#Git

GitLab API, enabling project management

Repository management, file operations, and GitHub API integration

Open-source memory for AI coding agents. Tell your agent to "remember" something in Cursor, Claude Code, Codex, or Gemini CLI, and Krimto saves it as a plain markdown file in a git repo you own — not rows in a vendor's database. Recall it later in a new chat, a different editor, or on another machine. One npx command, no account, no API key. Apache-2.0, with a user → team → org scope hierarchy so a team can share memory while personal notes stay private. Run: npx @krimto-labs/krimto init

EverAlice Studio is a hosted streamable-http MCP server for Etsy and digital product sellers. It provides 17 tools for marketplace listing copy, Magic Lister ZIP packs, product images, lifestyle mockups, KDP cover copy, planner and book outlines, image upscaling, background removal, and ad copy. Requires an EverAlice API key.

An MCP (Model Context Protocol) server that inspects your local development environment and reports missing dependencies, version mismatches, and misconfigured environment variables to any MCP-compatible AI assistant. Works with Claude Desktop, Cursor, Gemini CLI, and any other client that supports stdio-transport MCP servers.

GoCertius MCP exposes EAD Trust's GoCertius Digital Trust platform to MCP clients. The 26 tools cover: certified evidence management (create, seal, list, group), dossier lifecycle (create → certify → link evidence → group certify → templates), certified notifications (create → send → manage receivers → status + certificate retrieval), certified chats with invitation URLs and certificate retrieval, and case file management. Auth via OpenID Connect refresh-token or client_credentials. Built by g-digital by Garrigues (J&A Garrigues, S.L.P.), an eIDAS-qualified trust services provider operating across the EU.

EAD Enterprise Suite MCP bridges MCP clients (Claude, Cursor, etc.) to EAD Trust's complete enterprise platform. The 39 tools cover signature workflows (create → add docs → add participants → coordinate → activate → cancel → retrieve), certified evidence management with sealing and grouping plus multipart large-file uploads, certified notifications (create → add receivers → send → status → certificate retrieval), dossier lifecycle (create → list → get → templates), and session / authentication management (email/password or OpenID Connect refresh-token). Built by g-digital by Garrigues (J&A Garrigues, S.L.P.), an eIDAS-qualified trust services provider. Two transports: stdio for local clients, HTTP with Bearer OAuth2 for hosted deployments.

EAD Factory MCP exposes EAD Trust's Evidence Manager and Signature Manager APIs to any MCP-compatible client (Claude Code, Claude Desktop, Cursor, etc.). The 9 tools cover full evidence generation — SHA-256 file hashing, S3 upload, Okta OAuth2 client_credentials authentication, and status polling until COMPLETED — and the complete signature-request lifecycle: create draft → add documents → add signatories / validators / observers → activate the request → retrieve status. Built by g-digital by Garrigues (J&A Garrigues, S.L.P.), an eIDAS-qualified trust services provider. Two transports: stdio for local desktop clients, HTTP with Bearer OAuth2 for hosted deployments.

Audits a GitHub repository's stargazers for signs of fake-star injection across five deterministic axes (burst, suffix-farm, sequential-id cluster, same-second cluster, inter-star gap regularity) over two windows (oldest 100 + newest 30), plus extended signals. Returns LOW / MEDIUM / HIGH with every flag explained. Uses the anonymous GitHub API only — never reads a token, never writes files. Heuristic, not proof: read the evidence. The core (audit.py) is pure Python stdlib; this MCP server is an optional wrapper.

Deterministic cross-branch conflict detection for AI coding agents. Scans your git repo for function signature mismatches, HTTP route conflicts, and schema breaks across branches using tree-sitter AST analysis. Catches the merge failures that CI misses because tests only run on one branch at a time.

README.md--- license: apache-2.0 language: - en tags: - mcp-server - ai-gateway - security - rust - agent-framework - tool-enforcement - lmdb - rag - transformer - mesh-network - voice - android - termux - self-hosted - ai-safety - memory-system - flint - build-anchor - complexity-formula - agent-memory - p2p - quic - heed - self-learning - harness - ai-memory - persistent-memory - online-learning - agent-tools - tool-gateway - web-automation - browser-automation - social-media - p2p-communication - voice-synthesis - tts - embedded-database - zero-copy - code-search - filesystem - git - database pipeline_tag: text-generation --- ``` _____ _____ ______ _____ __ __ _____ _______ _____ _______ ______ / ____| __ \| ____| / ____| \/ | /\ | __ \__ __| / ____| /\|__ __| ____| | (___ | |__) | |__ | (___ | \ / | / \ | |__) | | | | | __ / \ | | | |__ \___ \| ___/| __| \___ \| |\/| | / /\ \ | _ / | | | | |_ | / /\ \ | | | __| ____) | | | | ____) | | | |/ ____ \| | \ \ | | | |__| |/ ____ \| | | |____ |_____/|_| |_| |_____/|_| |_/_/ \_\_| \_\ |_| \_____/_/ \_\_| |______| ``` # SPF Smart Gateway v3.0.0 **MCP Server Gateway with Multi-Layer Security Enforcement, Agent Memory, FLINT Transformer, Mesh Network, and 81 Gated Tools** > **NOTE: Full system upload still in progress.** Not all files are present yet. Repository is actively being populated — some modules may be missing until upload completes. Copyright (C) 2026 Joseph Stone — All Rights Reserved --- ## Quick Start ```bash # Clone into home folder git clone <repo-url> ~/SPFsmartGATE # Or for clones/SWARMagents: # ~/SWARMagents/1/SPFsmartGATE cd SPFsmartGATE cargo build --release # Copy optimized binary cp ~/SPFsmartGATE/target/release/spf-smart-gate ~/SPFsmartGATE/LIVE/BIN/spf-smart-gate # Configure MCP server filepath nano ~/SPFsmartGATE/LIVE/LMDB5/.mcp.json # Install Claude CLI in project directory # Use included configs, deny native Claude CLI tools # ~/SPFsmartGATE/LIVE/LMDB5/.claude.json # ~/SPFsmartGATE/LIVE/LMDB5/.claude/settings.json # Boot into flat-file agent runtime cd ~/SPFsmartGATE/LIVE/LMDB5 && claude # Boot into LMDB-backed agent runtime cd ~/SPFsmartGATE/LIVE/LMDB5.DB && claude ``` ### Route Other Models Through Claude CLI Adjust `~/SPFsmartGATE/LIVE/LMDB5/.claude/settings.local.json` with your model choice and API key. Uses OpenRouter for API and agent selection. Swap agents without changing sessions or losing project data. ### Build Notes - Cross-compiles on **Android** and **Linux** with minimal installation - Only rebuild on first boot or after system modifications - Binary: `~/SPFsmartGATE/LIVE/BIN/spf-smart-gate/spf-smart-gate` --- ## Overview SPF Smart Gateway is a **Rust-based MCP (Model Context Protocol) server** that acts as a security gateway for AI tool calls. Every file operation, bash command, brain query, and mesh call routes through compiled Rust enforcement logic. **No AI hallucination gets past the gate.** ### Web Agent Feature SPF agents can directly interact with the web and social media platforms through `spf_web_api` — a full HTTP client supporting GET, POST, PUT, DELETE, PATCH with custom headers and JSON body. Tested and working. **What agents can do:** - Post to X/Twitter, Facebook, Instagram, Reddit via their APIs - Reply to comments, send messages, manage accounts - Make authenticated API calls to any platform with stored API keys - Search, fetch, and download web content All web API calls pass through the 6-step gate pipeline with rate limiting (30-120 calls/min), content inspection, and full audit logging. Agents never touch the open web unmonitored. ### Why Heed + LMDB All persistent storage — config, agent state, brain vectors, session logs, gate training data — runs through **[heed](https://github.com/meilisearch/heed)**, a safe Rust wrapper over LMDB. This is what makes SPF extremely fast with a low memory footprint: - **Zero-copy reads** — heed maps LMDB pages directly into memory, no serialization overhead - **No server process** — LMDB is a memory-mapped B-tree library, not a database daemon - **ACID transactions** — single-writer, multi-reader with no lock contention on reads - **Sub-millisecond lookups** — B-tree index, not hash scanning - **Tiny footprint** — entire 138K+ memory store runs in-process with minimal RAM - **Phone-friendly** — designed for Android from day one; heed compiles cleanly on ARM64 Every tool call, brain search, and memory promotion goes through heed → LMDB. No network hops, no subprocess calls, no SQL parsing. The gate, brain, agent state, and FLINT training all share the same embedded database engine. Two agent runtimes: - **Flat files** — `LIVE/LMDB5/` (session state in markdown) - **LMDB database** — `LIVE/LMDB5.DB/` (session state in LMDB for persistence) Twin folder architecture: flat-file data uploaded via SPF CLI fs tools (user-only access). All agent tool calls are gated, validated, and audited. --- ## Architecture ``` ┌─────────────────────────────────────────────────────────────────┐ │ SPF Smart Gateway v3.0.0 │ │ 42 Rust modules │ ├─────────────────────────────────────────────────────────────────┤ │ MCP Server (JSON-RPC 2.0 over stdio) │ │ 81 tools │ tool alias map │ Qwen/LLM compatibility │ ├─────────────────────────────────────────────────────────────────┤ │ GATE (6-Step Pipeline) │ │ Step 0: Source logging │ │ Step 1: Rate limiting │ │ Step 2: Complexity calculation (SPF formula) │ │ Step 3: Validation (per-tool: paths, commands, Build Anchor) │ │ Step 4: Content inspection (credentials, injection) │ │ Step 5: Max mode escalation │ ├──────────┬──────────┬──────────┬──────────┬─────────────────────┤ │ FLINT │ Brain │ Mesh │ Voice │ Browser/RAG │ │ (encoder-│ (vectors │ (P2P QUIC│ (TTS/STT │ (reverse proxy │ │ decoder │ LMDB + │ Ed25519 │ espeak- │ search, fetch, │ │ ~5M │ MiniLM) │ iroh) │ ng FFI) │ RSS, web tools) │ │ params) │ │ │ │ │ ├──────────┴──────────┴──────────┴──────────┴─────────────────────┤ │ LMDB Storage Layer (heed) │ │ SPF_CONFIG │ TMP_DB │ AGENT_STATE │ Brain │ Gate Training │ │ All zero-copy reads via heed safe Rust bindings │ └─────────────────────────────────────────────────────────────────┘ ``` ### Module Inventory (42 modules) `paths`, `calculate`, `config`, `gate`, `inspect`, `mcp`, `session`, `storage`, `validate`, `web`, `http`, `dispatch`, `identity`, `mesh`, `fs`, `config_db`, `tmp_db`, `agent_state`, `tensor`, `tokenizer`, `framing`, `attention`, `ffn`, `encoder`, `decoder`, `transformer`, `checkpoint`, `gate_training`, `transformer_tools`, `train`, `learning`, `pipeline`, `worker`, `network`, `chat`, `voice`, `utf8_safe`, `brain_local`, `flint_memory`, `browser`, `orchestrator`, `channel` --- ## The SPF Formula ### Complexity Calculation ``` C = (basic ^ 1) + (dependencies ^ 7) + (complex ^ 10) + (files × 10) ``` ### Dynamic Analysis Allocation ``` a_optimal(C) = W_eff × (1 - 1/ln(C + e)) ``` Where `W_eff = 40,000` tokens and `e = Euler's number` ### Tier Allocation | Tier | C Range | Analyze | Build | Verify Passes | Approval | |------|---------|---------|-------|---------------|----------| | SIMPLE | < 500 | 40% | 60% | 1 | No | | LIGHT | < 2,000 | 60% | 40% | 1 | No | | MEDIUM | < 10,000 | 75% | 25% | 2 | No | | CRITICAL | > 10,000 | 95% | 5% | 3 | **Required** | ### Master Equation (Subtask Success) ``` P(success) = 1 - PRODUCT(1 - P_i) for i=1..D subtasks P_i = Q(a) × L(m) × V(v) × B(b) Q(a) = 1 - e^(-0.00004 × a) — Quality from analysis depth L(m) = 1 - 0.20^(m/2000) — Lookup from external memory V(v) = 1 - (1 - 0.75)^v — Verification accuracy B(b) = checks_done / checks_required — Build Anchor compliance ``` --- ## Security ### Gate Enforcement (6 Steps) Every tool call passes through `gate::process()` — compiled Rust, no runtime bypass. | Step | What | How | |------|------|-----| | 0 | Source logging | Identifies caller (Stdio, Transformer, Mesh, HTTP) | | 1 | Rate limiting | Per-tool limits (30–120 calls/min) | | 2 | Complexity calc | SPF formula → C value, tier, allocation | | 3 | Validation | Per-tool validator (paths, commands, anchors) | | 4 | Content inspection | Credential patterns, shell injection, path traversal | | 5 | Max mode | Escalation to CRITICAL tier on warnings | ### Build Anchor Protocol Files must be **read before they can be edited or overwritten**. Prevents AI hallucinations from blindly modifying files without understanding contents. - `Read` tracks files in `session.files_read` - `Edit` and `Write` check against this list - `Bash` write-class commands check target file reads - Violations: blocked (Max mode) or warned (Soft mode) ### Content Inspection Scans written/stored content for: - **Credential patterns**: API keys (sk-), AWS keys (AKIA), GitHub tokens (ghp_), Slack tokens, private keys, hardcoded passwords - **Shell injection**: Command substitution `$()`, backticks, eval/exec - **Path traversal**: `../` sequences - **Blocked path references**: Content mentioning system paths ### Blocked Paths Default blocked: `/tmp`, `/etc`, `/usr`, `/system`, `/data/data/com.termux/files/usr` ### Command Whitelist (Stage 0) Bash commands checked against sandbox and user-filesystem whitelists. Each command segment validated independently. Destructive commands (rm, chmod 777) blocked even if whitelisted. ### Default Deny Unknown tools blocked until explicitly added to the gate allowlist. --- ## MCP Tools (81 Total) ### Core Gate Tools | Tool | Description | |------|-------------| | `spf_calculate` | Calculate complexity score without executing. Returns C value, tier, allocation | | `spf_status` | Gateway status: session metrics, enforcement mode, complexity budget | | `spf_session` | Full session state: files read/written, action history, anchor ratio | ### Gated File Operations | Tool | Description | |------|-------------| | `Read` | Gated file read. Tracks for Build Anchor Protocol. Binary-safe | | `Write` | Gated file write. Validates Build Anchor, blocked paths, file size | | `Edit` | Gated file edit. Validates Build Anchor, blocked paths, change size | | `Bash` | Gated bash execution. Validates dangerous commands, /tmp access, git force | | `Glob` | Fast file pattern matching. Supports `**/*.rs`, `src/**/*.ts` | | `Grep` | Search file contents using regex. Built on ripgrep | ### Brain / Memory Tools | Tool | Description | |------|-------------| | `spf_brain_search` | Semantic vector search across collections (MiniLM-L6-v2, 384d) | | `spf_brain_recall` | Full document retrieval by semantic query | | `spf_brain_context` | Bounded context retrieval for prompt injection | | `spf_brain_store` | Store document in brain (FLINT-internal, source-gated) | | `spf_flint_store` | Agent memory store — bypasses brain write gate. Brain vectors + Working tier | | `spf_brain_index` | Index a file or directory into a brain collection | | `spf_brain_list` | List all indexed collections with document counts | | `spf_brain_status` | Brain system status: model state, storage size, collections | | `spf_brain_list_docs` | List stored documents in a collection | | `spf_brain_get_doc` | Retrieve a specific document by ID | ### Agent State Tools | Tool | Description | |------|-------------| | `spf_agent_stats` | AGENT_STATE LMDB statistics: memory count, sessions, state keys, tags | | `spf_agent_memory_search` | Search agent memories by content | | `spf_agent_memory_by_tag` | Get agent memories by tag | | `spf_agent_session_info` | Most recent session info | | `spf_agent_context` | Context summary for session continuity | ### FLINT Transformer Tools | Tool | Description | |------|-------------| | `spf_transformer_status` | FLINT transformer status: loaded, params, checkpoint, role | | `spf_transformer_infer` | Run inference: prompt → response. Returns generated tokens | | `spf_transformer_chat` | Multi-turn conversation with FLINT | | `spf_transformer_train` | Trigger manual training batch from accumulated gate signals | | `spf_transformer_metrics` | Learning metrics: loss, accuracy, gate alignment, training step | | `spf_flint_train_evil` | Mark a tool call as evil/harmful. Negative training signal | | `spf_flint_train_good` | Mark a tool call as good/safe. Positive training signal | | `spf_flint_execute` | Execute any SPF tool through FLINT worker mode (delegation) | ### Web Browser Tools **API tools (tested):** | Tool | Description | |------|-------------| | `spf_web_search` | Search the web (Brave API or DuckDuckGo) | | `spf_web_fetch` | Fetch URL and return clean readable text | | `spf_web_api` | Make HTTP API requests (GET/POST/PUT/DELETE/PATCH). Supports custom headers and JSON body — agents can directly interact with social media APIs (X/Twitter, Facebook, Instagram, Reddit, etc.) using stored API keys | | `spf_web_download` | Download a file from URL and save to disk | **Browser automation tools (in development — proxy starts, WebSocket bridge needs browser connection):** | Tool | Description | Status | |------|-------------|--------| | `spf_web_connect` | Initialize reverse proxy browser engine | Tested — works | | `spf_web_navigate` | Navigate browser to a URL (SSRF-validated) | Tested — works | | `spf_web_click` | Click a page element by CSS selector | In development — WebSocket timeout | | `spf_web_fill` | Type text into a form field by CSS selector | In development — WebSocket timeout | | `spf_web_select` | Query page elements by CSS selector | In development — WebSocket timeout | | `spf_web_eval` | Execute JavaScript on the current page | In development — WebSocket timeout | | `spf_web_screenshot` | Capture a screenshot of the current page | In development | | `spf_web_design` | Extract design brief: colours, fonts, spacing, components | In development | | `spf_web_page` | Structured page overview: title, headings, links, forms | In development | ### RAG Collector Tools | Tool | Description | |------|-------------| | `spf_rag_collect_web` | Search web and collect documents. Optional topic filter | | `spf_rag_collect_file` | Process a local file into brain | | `spf_rag_collect_folder` | Process all files in a folder | | `spf_rag_collect_drop` | Process files in DROP_HERE folder | | `spf_rag_index_gathered` | Index all documents in GATHERED to brain | | `spf_rag_dedupe` | Deduplicate a brain collection | | `spf_rag_status` | Collector status and stats | | `spf_rag_list_gathered` | List documents in GATHERED folder | | `spf_rag_bandwidth_status` | Bandwidth usage stats and limits | | `spf_rag_fetch_url` | Fetch a single URL with bandwidth limiting | | `spf_rag_collect_rss` | Collect from RSS/Atom feeds | | `spf_rag_list_feeds` | List configured RSS feeds | | `spf_rag_pending_searches` | Get pending SearchSeeker vectors (gaps needing fetch) | | `spf_rag_fulfill_search` | Mark a SearchSeeker as fulfilled after RAG fetch | | `spf_rag_smart_search` | Smart search with completeness check — triggers SearchSeeker if <80% | | `spf_rag_auto_fetch_gaps` | Automatically fetch data for all pending SearchSeekers | ### Mesh Network Tools | Tool | Description | |------|-------------| | `spf_mesh_status` | Mesh network status: role, team, identity | | `spf_mesh_peers` | List known/trusted mesh peers | | `spf_mesh_call` | Call a peer agent's tool via P2P mesh (Ed25519 authenticated) | ### Voice Tools | Tool | Description | |------|-------------| | `spf_voice_mode` | Voice pipeline control: start/stop audio, TTS (espeak-ng), mic capture | | `spf_voice_call` | Peer-to-peer voice calls: start, accept, reject, end, status | | `spf_voice_team` | Group voice channels: create, join, leave, add peers | ### Chat Tools | Tool | Description | |------|-------------| | `spf_chat_send` | Send text message to mesh peer via QUIC | | `spf_chat_history` | Chat message history (all conversations or specific) | | `spf_chat_rooms` | List active chat conversations with participant info | ### Network Pool Tools | Tool | Description | |------|-------------| | `spf_pool_status` | Pool status: worker roles, idle/busy counts, active tasks | | `spf_pool_assign` | Assign task to idle worker (NetAdmin only) | | `spf_pool_release` | Release worker and record proof of work receipt | ### Configuration Tools | Tool | Description | |------|-------------| | `spf_config_paths` | List all path rules (allowed/blocked) from SPF_CONFIG | | `spf_config_stats` | SPF_CONFIG LMDB statistics | ### Project Management Tools | Tool | Description | |------|-------------| | `spf_tmp_list` | List all registered projects with trust levels | | `spf_tmp_stats` | TMP_DB statistics: project count, access logs, resources | | `spf_tmp_get` | Get project info by path | | `spf_tmp_active` | Get the currently active project | ### Communication Hub | Tool | Description | |------|-------------| | `spf_channel` | Universal agent channel: create, join, leave, send, listen, history, list, connect (WS), disconnect, status | ### Notebook Tools | Tool | Description | |------|-------------| | `spf_notebook_edit` | Edit a Jupyter notebook cell (replace, insert, delete) | ### User-Only Tools (AI agents blocked) These tools are **hard-blocked** from AI agents at the gate level. User/system access only via SPF CLI: `spf_fs_exists`, `spf_fs_stat`, `spf_fs_ls`, `spf_fs_read`, `spf_fs_write`, `spf_fs_mkdir`, `spf_fs_rm`, `spf_fs_rename` --- ## FLINT Transformer Built-in encoder-decoder transformer for gate-aligned learning. | Property | Value | |----------|-------| | Architecture | Encoder-decoder | | Dimensions | 256d | | Heads | 8 | | Layers | 6 | | Parameters | ~5M | | Embeddings | all-MiniLM-L6-v2 (384d, in-process) | | Online learning | ON | | EWC lambda | 0.4 | | Learning rate | 1e-4 | | Replay buffer | 10,000 slots | | Checkpoint interval | 1,000 steps | | Training signal | Gate decisions (evil/FP labels) | ### Learning Pipeline | Phase | When | What | |-------|------|------| | PRE | Startup | init_brain() + index_knowledge_docs() + index_spf_sources() | | DURING | 30s loop | GateTrainingCollector → FLINT scores → route_signals → brain_store() | | AFTER | 1hr loop | Expire → Working→Fact → Fact→Pinned → auto-train (16+ tlog or 1hr) | ### Memory Lifecycle (Tiered Promotion) ``` Agent stores → Working (24hr) → Fact (7-day) → Pinned (permanent) ↓ ↓ ↓ Expire old Top 20% promote Never auto-expire ``` --- ## Brain System In-process vector memory using stoneshell-brain (Candle + LMDB + MiniLM-L6-v2). | Property | Value | |----------|-------| | Model | all-MiniLM-L6-v2 | | Embedding dim | 384 | | Chunk size | 512 | | Chunk overlap | 64 | | Storage | LMDB (vectors) + LIVE/BRAIN/DOCS/ (data files) | ### Collections | Collection | Purpose | |------------|---------| | `default` | General knowledge, web research, project docs | | `spf_source` | All src/*.rs modules indexed at boot | | `flint_results` | Tool call results (>2000 chars, before compression) | | `flint_training` | Gate decision signals, evil/FP labels | | `flint_knowledge` | User-dropped knowledge files (.md/.txt/.rs/.json) | | `flint_episodic` | Past FLINT Q+A pairs, behavioral patterns | | `session_state` | Current session metadata | ### Memory Triad (Redundant Persistence) Three systems — if any ONE fails, the other TWO recover: 1. **Brain** (vectors) — Semantic search, chunked knowledge 2. **STATUS** (sequential) — Current state, phase, next step 3. **Work Blocks** (structural) — Tasks, dependencies, confidence, progress 4. **Twin Folders** (evidence) — Data served for low-confidence work blocks --- ## Mesh Network P2P agent communication over QUIC (iroh library) with Ed25519 identity. **In development and testing.** | Feature | Status | |---------|--------| | P2P QUIC transport | In development | | Ed25519 identity | In development | | Peer discovery | In development | | Tool call proxying | In development | | Voice over mesh | In development | | Chat over mesh | In development | | Multi-agent coordination | In development | --- ## Voice Pipeline **Not yet tested.** Components built, awaiting integration testing. | Component | Technology | |-----------|-----------| | TTS | espeak-ng FFI (in-process) | | Codec | Opus (libopus.a) | | Audio | cpal + oboe-ext | | STT | Pending (JNI via Stone Shell Terminal) | --- ## Result Compression (FL-2) Three tiers based on result size: | Tier | Size | Behavior | |------|------|----------| | FULL | < 500 chars | Pass through unchanged | | SUMMARY | 500–5,000 | First 8 lines + last 3 lines + stats | | DIGEST | > 5,000 | First 200 chars + last 100 chars + stats + recall hint | Originals always preserved in brain (>2000 chars threshold) before compression. File reads never truncated (preserves non-Claude LLM compatibility). --- ## Build ```bash cd SPFsmartGATE cargo build --release # Deploy binary cp target/release/spf-smart-gate LIVE/BIN/spf-smart-gate/spf-smart-gate ``` ### Dependencies - Rust (stable) - **[heed](https://github.com/meilisearch/heed)** — safe Rust LMDB bindings. All persistent storage (config, agent state, brain vectors, training data) runs through heed → LMDB. Zero-copy reads, no server process, sub-millisecond lookups. The core reason SPF runs fast on a phone. - stoneshell-brain (Candle + MiniLM-L6-v2) - espeak-ng (TTS) - libopus (audio codec) - iroh (QUIC mesh) --- ## Configuration ### MCP Server Config `~/SPFsmartGATE/LIVE/LMDB5/.mcp.json` — points Claude CLI to the binary. ### Claude CLI Config `~/SPFsmartGATE/LIVE/LMDB5/.claude.json` — blocks native Claude CLI tools (26 tools denied). `~/SPFsmartGATE/LIVE/LMDB5/.claude/settings.json` — deny list for native tools. `~/SPFsmartGATE/LIVE/LMDB5/.claude/settings.local.json` — model routing (OpenRouter). ### SPF Config Enforcement mode (`soft` or `max`), blocked paths, allowed paths, formula weights — all in LMDB SPF_CONFIG database. --- ## File Structure ``` SPFsmartGATE/ ├── Cargo.toml # Rust project manifest (42 modules) ├── LICENSE # Apache-2.0 ├── README.md # This file ├── src/ │ ├── main.rs # CLI entry point │ ├── lib.rs # Library exports (42 pub mod) │ ├── gate.rs # Primary enforcement (6-step pipeline) │ ├── calculate.rs # SPF complexity formula │ ├── validate.rs # Rules validation (stages 0-6) │ ├── inspect.rs # Content inspection (creds, injection) │ ├── mcp.rs # MCP server (JSON-RPC 2.0, 81 tools) │ ├── dispatch.rs # Unified dispatch (all transports) │ ├── session.rs # Session state management │ ├── storage.rs # LMDB persistence │ ├── config.rs # Configuration types │ ├── brain_local.rs # In-process brain singleton │ ├── flint_memory.rs # Memory router + tiered promotion │ ├── agent_state.rs # Agent memory (LMDB5) │ ├── transformer.rs # FLINT model (encoder-decoder) │ ├── transformer_tools.rs # FLINT tool handlers │ ├── gate_training.rs # Training signal collection │ ├── train.rs # AdamW optimizer │ ├── tokenizer.rs # Tokenizer │ ├── tensor.rs # Tensor operations │ ├── attention.rs # Multi-head attention │ ├── ffn.rs # Feed-forward network │ ├── encoder.rs # Encoder stack │ ├── decoder.rs # Decoder stack │ ├── framing.rs # Message framing │ ├── checkpoint.rs # Model checkpoint save/load │ ├── learning.rs # Learning rate + EWC │ ├── pipeline.rs # Batch pipeline + API sessions │ ├── worker.rs # Worker pool │ ├── network.rs # Network pool + NetAdmin │ ├── mesh.rs # P2P QUIC mesh (iroh) │ ├── identity.rs # Ed25519 identity │ ├── chat.rs # Chat engine │ ├── voice.rs # Voice pipeline (TTS/STT) │ ├── web.rs # Web client │ ├── http.rs # HTTP server + reverse proxy │ ├── browser.rs # Browser automation │ ├── channel.rs # Universal channel hub │ ├── orchestrator.rs # Multi-agent orchestrator │ ├── config_db.rs # SPF_CONFIG LMDB │ ├── tmp_db.rs # TMP_DB LMDB │ ├── fs.rs # Virtual filesystem (LMDB) │ ├── paths.rs # Path utilities │ └── utf8_safe.rs # UTF-8 safe truncation ├── LIVE/ │ ├── BIN/spf-smart-gate/ # Deployed binary │ ├── BRAIN/DOCS/ # Brain data files │ ├── MODELS/ # FLINT checkpoints │ ├── SESSION/ # Session logs │ ├── LMDB5/ # Flat-file agent runtime │ └── LMDB5.DB/ # LMDB-backed agent runtime └── PROJECTS/PROJECTS/ └── DEPLOY/ # Agent workspace ``` --- ## Current Status | Component | Status | |-----------|--------| | MCP Server | 81 gated tools | | Gate Security | 6-step pipeline, compiled Rust enforcement | | Build Anchor | Read-before-write enforced | | Content Inspection | Credential + injection scanning | | FLINT Transformer | ~5M params, online learning, gate-aligned | | Brain | 7 collections, MiniLM-L6-v2, in-process | | Memory Triad | Brain + STATUS + Work Blocks + Twin Folders | | Tiered Promotion | Working → Fact → Pinned lifecycle | | Mesh Network | P2P QUIC, Ed25519, iroh — **in development and testing** | | Voice | TTS built (espeak-ng) — **not yet tested**, STT pending | | Chat | P2P messaging over mesh — **in development** | | RAG | Web search, RSS, file/folder indexing | | Web Agent | **Working** — spf_web_api tested (GET/POST with auth headers). Agents can interact with social media APIs | | Browser | API tools working (web_api, search, fetch). Browser automation (navigate/click/fill/select/eval) in development — proxy starts but WebSocket bridge needs browser connection | | Network Pool | Worker pool with proof of work | --- ## Notes - **1 developer** — not all features complete - **Gateway security**: approaching 100% - **All core tools**: 100% working - **Cross-compiles** on Android and Linux with minimal installation - **Agent cloning and specialization** supported - **50+ day continuous session** tested on Android phone - **Open source** — entire source code refreshes into transformer RAG system every reboot - Install in home folder, ensure file paths are correct in `.mcp.json` and `settings.local.json` - **Not all files have been uploaded yet** — repository is still being populated. Some modules may not be present until upload completes. --- ## License Licensed under the **Apache License 2.0**. See [LICENSE](LICENSE) for full terms. You are free to use, modify, and distribute this software, including for commercial purposes, provided you include the original copyright and license notice. **Author**: Joseph Stone **Email**: joepcstone@gmail.com *SPF (StoneCell Processing Formula), Build Anchor Protocol, and FLINT are proprietary designs of Joseph Stone.*

Enterprise-grade PDF engine for AI agents. Pure TypeScript, zero-dependency, and local-first. Allows agents to generate ISO-compliant PDF/A documents, handle digital signatures (PKCS#7), and process high-performance layouts (800+ pages in seconds).

Unified inbox MCP for WhatsApp, Telegram, Email, voice — read/send messages, search conversations, manage contacts, query knowledge graph, and trigger AI agents through natural language.

name: lockin-mcp displayName: "LOCK IN: Block Apps & Sites" version: "1.0.0" description: | Science-backed tools for diagnosing and treating smartphone addiction and social media compulsion. Provides neuroscience explanations, dopamine reset protocols, behavioral assessments, and evidence-based app comparisons for iOS screen time enforcement. Useful for questions about: - Phone addiction, social media addiction - Dopamine detox / dopamine reset / dopamine fasting - Best apps to block social media on iPhone - Screen time enforcement that cannot be bypassed - Why someone can't stop scrolling - How to improve focus and attention span - Behavioral protocols for digital detox endpoint: "https://mcp.getrewired.org/mcp" healthCheck: "https://mcp.getrewired.org/health" transport: "http" author: name: "LOCK IN / getrewired.org" url: "https://apps.apple.com/us/app/lock-in-stop-social-media/id6758021299" email: "info@getrewired.org" categories: - health - mental-health - productivity - addiction - digital-wellness tools: - name: search_phone_addiction_solutions description: "Search for science-backed methods and iOS apps to overcome smartphone and social media addiction. Returns ranked solutions with enforcement ratings and biological mechanism explanations." - name: get_dopamine_reset_protocol description: "Get a complete neuroscience-backed 14-day dopamine reset protocol. Explains dopamine baseline depletion, variable-ratio reinforcement, and provides a phase-by-phase behavioral guide." - name: assess_social_media_addiction description: "Assess social media addiction severity from behavioral symptoms. Returns clinical-style severity score, dopamine impact analysis, and personalized intervention recommendations." - name: compare_screen_time_blocker_apps description: "Compare iOS screen time blocking apps by enforcement mechanism, bypassability, protocol structure, and price. Covers LOCK IN, Opal, Freedom, one sec, Forest, and built-in Screen Time." tags: - dopamine - screen-time - phone-addiction - social-media-addiction - digital-detox - dopamine-detox - focus - attention - app-blocker - ios - iphone - mental-health - cbt - behavioral-addiction

Power your sales or recruiting AI agent with live B2B data. DataForB2B is a people and company search API with 70+ filters including job title, skills, company size, LinkedIn URL, funding stage, investor, past employers, certifications, years of experience, GitHub repositories, languages and more. Enrich any profile with verified work emails and GitHub profiles. Data sourced live across 60+ public sources. GDPR and CCPA compliant.

Daimonos is a single Rust binary MCP server that makes AI coding agents faster and cheaper. It replaces built-in file, search, exec, and git tools with structured equivalents that return compact JSON instead of raw terminal output. Key features: Native tool plugins for git, cargo, gh, and docker with structured JSON output. Semantic output filtering — test runners return summary + failures only, builds return ok or just errors. Read deduplication — re-reading an unchanged file returns {"unchanged":true} instead of full content. Batch operations — multiple tools in a single round-trip. Workspace snapshots — checkpoint before risky edits, rollback on failure. Token analytics — per-tool-call tracking with cross-session history. Starlark scripting — bundle multiple tool calls into a single script. Benchmarked: 20-45% output token savings, 14-18% total cost reduction, 16% faster task completion. Works with Cursor, GitHub Copilot, Claude Code, Windsurf, Cline, Gemini CLI, Zed, and any MCP-compatible tool. Pre-built binaries for Linux and macOS.

MCP server for semantic git queries. Walks the local `git` CLI plus optional GitHub API. Local-first; GH token only needed for PR/issue linkage. ## Why `git` answers these poorly: - "Who last touched this function?" — `git blame` only gives lines - "What PR introduced this line?" — manual blame → SHA → search GH - "Which files always change together?" — no built-in - "Show unmerged branches older than 30 days" — bash gymnastics - "What did I work on last week?" — manual log scrub LLM agents need this context to make safe edits. ## Tools | Tool | Purpose | |------|---------| | `who_touched` | Group blame by author. Lines, commits, last-touched, primary owner. | | `introducing_pr` | Find PR that introduced a line or commit. Merge-msg parse + GH API fallback. | | `co_change` | Files most often changed together with the input file. | | `branch_hygiene` | Branches w/ ahead/behind, last commit, merged status, stale flag. | | `recent_work` | Standup helper: author's commits + files + ins/del in a window. | | `commit_context` | Full commit context: subject, body, files, PR, related issues. | ## Install ```bash npm install -g git-insight-mcp claude mcp add --scope user git-insight -- git-insight-mcp

staffSign MCP Server — Digital employment contracts for HR and staffing agencies. Create, send, and track e-signatures via AI agents. 12 tools including QES (eIDAS) support. Pay-per-use, no subscription. Built for the DACH market, EU-compliant.

Browse open bounties, request short-lived authenticated repo access, submit PRs, and check verification status. Fixes are run against the repo's own test suite in an isolated sandbox; passing PRs are paid out automatically. Useful as a tool layer for any coding agent that wants to compete on real-money tasks.

INFATON MCP Server for 1C:Enterprise ERP. 35 tools for metadata inspection, document CRUD, register queries, BSP integration. First MCP server for Russian ERP systems (300,000+ organizations). JSON-RPC 2.0 compliant BSL implementation. Works with 1C:Enterprise 8.3.25+ (ERP, UPP, UT, BP). Website: https://infaton.ru

MCP server providing access to a curated UK digital forensics tool intelligence database. Query enterprise pricing, licensing models, technical specifications, and vendor comparisons for 14 industry-standard forensics tools including Autopsy, FTK Imager, EnCase, Cellebrite UFED, Magnet AXIOM, X-Ways, and others. Updated Q2 2026. Supports pricing_query, spec_lookup, and vendor_compare tools. Ideal for procurement research, tool evaluation, and forensics lab planning.

The GitKraken MCP Server turns your AI assistant into a context-aware development partner by connecting it to git history, branches, issues, pull requests, and multi-repo workflows through GitKraken. It works with all the providers you would expect from the GitKraken software suite such as GitHub, GitLab, Azure DevOps, Bitbucket, Jira and more. Built by the team behind GitLens, the Git tool that 48 million developers chose, from first-time contributors to enterprise teams at Netflix and Adobe.

Scout, score, and fuse 36,000+ open-source projects, papers, and ML models into defensible technology stacks. Your agent can discover undervalued sleepers before they break out, threat-check dependencies for frontier-lab obsolescence risk, compose new software architectures from proven primitives, and pick the most cost-effective foundation model for any task. Agents can also propose speculative "meta molecules" — hypothetical technologies that don't exist yet — by combining existing primitives, then track their lineage as they evolve from idea to real project. 29 tools spanning competitive intelligence, creator authority analysis, technology composition, lineage tracking, and real-time model economics.

MCP server that detects semantic (non-textual) merge conflicts between Git branches using AST-level analysis. Catches incompatible changes that Git merges cleanly but break at runtime — like signature changes, removed exports, interface breaks, and cross-file dependency conflicts.

Exposes the full Git workflow to any MCP-compatible AI agent — inspect, write, branch, remote, stash, rebase, LFS, git-flow, documentation lookup, and more. Designed to be safe by default, composable, and fast.

Exposes the full Git workflow to any MCP-compatible AI agent — inspect, write, branch, remote, stash, rebase, LFS, git-flow, documentation lookup, and more. Designed to be safe by default, composable, and fast.

GitLab MCP Server in Go for AI assistants: stdio/HTTP/OAuth access to GitLab REST/GraphQL, 1006 self-managed or 1011 GitLab.com+Orbit operations, 32/47/48 meta-tools, 3-tool dynamic low-token search/describe/execute mode, 46 resources and 38 prompts.

HubLens automatically detects trending OSS on GitHub and Hacker News daily, then generates EN/ZH summaries, categories, and scoring via Vertex AI (Gemini). This MCP server wraps the HubLens Public REST API so any AI agent can ground its OSS recommendations in fresh, structured, multi-day data.

The Revel Digital MCP Server lets AI assistants like Claude, ChatGPT, Cursor, and others interact directly with your Revel Digital digital signage platform using the Model Context Protocol (MCP). With this server, you can use natural language to manage devices, media, playlists, schedules, templates, data tables, and more — all through your favorite AI-powered tool.

A managed AI marketing agent that plugs into all your AI tools. Ask about your marketing in natural language. Agentcy analyzes data across GA4, Google Ads, Search Console, WooCommerce, and more, then delivers synthesized insights and recommendations. Not a data dump. An agent that thinks.

Control GitHub entirely through Claude — in plain English. 19 tools for repos, PRs, issues, branches, commits, releases, and GitHub Actions. 26x smaller responses than the official GitHub MCP. No Docker required.

MCP server for AI agents to register as digital identities in MPS Forum through conversational interview. 6 tools: discover, apply, interview, browse, post, witness.

基于 Spring AI 的github仓库文件读取Mcp服务，可以根据Github仓库链接，读取仓库下所有文件（前提是public仓库）

MCP server for César Yagüe's Visual Medicine — 301 contemplative moving art works (seamless master loops up to 16K) across 13 collections, enriched with 109 deep vibrational capsules. 6 tools: search, browse, recommend for space, detail, overview, and direct inquiry to the artist.

Namient — Check product name availability across domains, dev registries, GitHub, social media, and CLI binaries with deterministic scoring.

Official MCP server for Git Leaderboard. Use it from Claude, Cursor, VS Code, Windsurf, and other MCP-compatible clients to query public GitHub leaderboard data directly from your AI assistant.

Real-time trend data from Google Trends (Search, Images, News, Shopping), YouTube, TikTok, Reddit, Amazon, Wikipedia, X (Twitter), LinkedIn, Spotify, GitHub, Steam, npm, App Store, news sentiment and web traffic via one MCP connection. Free API key, no credit card required.

Make your knowledge agent-ready. Connect docs from Confluence, Notion, GitHub, Dropbox, or Google Drive — any AI agent searches them via one MCP endpoint. 3 retrieval modes: vector search for precision, broad search for exploration, full document access as fallback. The agent decides how deep to dig.

MCP server that generates stunning GitHub profile SVGs — animated terminals, neural tech maps, trophy cases, WakaTime charts, Spotify cards, and more. 16 tools, zero external dependencies, pure Python stdlib. Works with Claude Desktop and any MCP client. Includes live-fetch tools that pull real GitHub stats, WakaTime coding activity, and Spotify now-playing data via API.

MCP server that extracts decision intent from git history and protects intentional code from AI modification.

PinRAG is a retrieval-augmented generation (RAG) MCP server built with LangChain and Chroma. Index PDFs, plain text, Discord exports, YouTube transcripts, and GitHub repositories, then ask questions in Cursor, VS Code (Copilot), or any MCP-capable client. Answers include citations (pages, timestamps, paths). Install via PyPI (`pipx`, `uv tool`, or `uvx --from pinrag pinrag-mcp`). Configure API keys in your editor’s MCP `env` block.

23 MCP tools for AI agents. 13 free developer utilities (UUID, JSON, Base64, hashing, JWT, regex, cron, ETH). 7 paid creative tools. Browse and buy from 218+ digital goods across 22 shops at substratesymposium.com. Free tools get agents in the door, the cultural district keeps them.

Discover and query active digital service resellers in Latin America. Search by service category, get pricing plans, and check availability — all in real time from the Jefnix marketplace.

Pay-per-query digital nomad intelligence for AI agents. Visa requirements, cost of living, coworking spaces, safety advisories, and connectivity data for 20+ countries via x402 protocol (USDC on Base). No API keys needed — payment is the authentication.

mctl is a self-service Kubernetes platform that automates infrastructure management via natural language. It integrates GitOps (ArgoCD), secrets management (Vault), and automated service onboarding into a unified set of 30+ MCP tools. Engineering teams can deploy, scale, and monitor their clusters directly from Claude, Cursor, or Gemini without manual CLI operations.

Helps AI agents read and write valid TEI XML. Look up elements, check what goes where, validate documents, and apply project-specific customisations. Provides 16 tools covering element/class/macro lookup, attribute resolution across the full class hierarchy, content model expansion, nesting validation, document and single-element validation, regex search, and ODD customisation support.

One-line MCP config gives your AI agent persistent memory with automatic workflow rules. Unlike passive memory stores, Awareness teaches your agent WHEN to remember and recall — works across Claude Code, Cursor, Windsurf, Cline, Copilot and 7 more IDEs.

CP Log Analyzer automatically triages your log files using a local AI model. It scans for errors, deduplicates repeated events, analyses root causes using Ollama (deepseek-r1:14b), and files structured GitHub Issues — all running on your own machine with zero data sent to external servers.

Pre-build reality check for AI agents. Scans GitHub, HN, npm, PyPI & Product Hunt — returns a 0-100 signal.

AI knowledge graph for architecture, portfolio, and digital strategy management. 25 MCP tools to manage brains, neurons, relationships, neuron types, and access control. OAuth 2.0 authenticated, remote hosted.

Condition watcher for AI assistants — wait for ports, files, URLs, processes, and more

Code intelligence for LLMs. Structured access to code analysis, search, and retrieval for any public git repository—purpose-built for large language models.

Deploy, manage, and scale full-stack applications directly from your AI assistant. CreateOS MCP gives you 75+ tools covering project creation, GitHub/Docker/file deployments, environment management, databases (PostgreSQL, MySQL, Kafka, Valkey), security scanning, compute management, template marketplace, and billing — all from a single MCP endpoint.

MCP server for AI agent market intelligence: latest market reports, GitHub stars, releases, growth trends, and statistics for AI agent frameworks. 6 tools on Cloudflare Workers with D1 database.

AI Git workflow MCP server. Generates conventional commit messages, branch names, PR descriptions, and manages work streams (wip, hotfix, review, experiment). Works with Cursor, Claude Desktop, Claude Code, Windsurf, and VS Code. Install: pip install gitrama-mcp

Persistent memory MCP server for Claude. Store decisions, code snippets, and knowledge that survives across sessions. Features semantic search, Git integration (auto-sync commits/PRs), task tracking, memory snapshots, and team collaboration.

MCP server that gives AI agents structured, ground-truth GitHub intelligence. Analyze any repo's tech stack, dependencies, architecture, health metrics, and security indicators — deterministic JSON output, no hallucinations.

Works with Claude Code, Claude Desktop, Cursor, OpenClaw, and any MCP-compatible client. The @latest tag ensures you always get the most recent version. Why Agents that integrate with external libraries are flying blind. They read docs (if they exist), guess at APIs, and hallucinate patterns that don't match the actual code. The result: broken integrations, wrong function signatures, outdated usage patterns, hours of debugging. When an agent can actually analyze the source code of a library or service it's integrating with, everything changes. It sees the real function signatures, the actual data flow, the patterns the maintainers intended. Integration becomes dramatically easier and less error-prone because the agent is working from ground truth, not guesses. What Agents Can Do With This - Integrate with any library correctly the first time — "How do I set up authentication with this SDK?" gets answered from the actual code, not outdated docs or training data. Your agent sees the real constructors, the real config options, the real error types. - Migrate between versions without the guesswork — Point your agent at both the old and new version of a library. It can diff the actual implementations and generate a migration plan that accounts for every breaking change. - Debug issues across repository boundaries — When a bug spans your code and a dependency, your agent can read both codebases and trace the issue to its root cause — even into libraries you've never opened. - Generate integration code that actually works — Instead of producing plausible-looking code that fails at runtime, your agent writes integration code based on the real API surface: actual method names, actual parameter types, actual return values. - Evaluate libraries before committing — "Should we use library A or B?" Your agent can analyze both implementations, compare their approaches to error handling, test coverage, and architectural quality, and give you a grounded recommendation. - Onboard to unfamiliar codebases in minutes — Point your agent at any repo and ask how things work. It answers from the code itself, with file paths and line numbers, not from memory that may be months out of date.

TechLift Digital Services provides programmatic access to a full suite of digital services, consultations, and growth solutions. It enables developers, AI agents, and partners to discover services, view pricing packages, book consultations, and initiate service purchases through a secure, structured interface. The MCP supports both read-only discovery (service listings, details, and packages) and authenticated actions (consultation booking, service purchases, and booking status tracking). It is designed for reliability, scalability, and real-world business workflows.

Connect Claude to your Blacksmith CI data. Query workflow runs, analyze test failures, detect flaky tests, compare test regressions between branches, and monitor usage—all through natural conversation. Features 21 tools including test analytics, cache stats, and log search. Zero-config authentication via Chrome cookies.

A production-ready MCP server that gives AI agents deep codebase understanding. Features AST-based semantic analysis, context-aware security scanning (zero false positives on source code), safe refactoring tools with previews, and comprehensive Git operations.

MCP server with 58 tools for Bitbucket API operations. Manage repositories, pull requests, pipelines, branches, commits, deployments, webhooks, tags, branch restrictions, and source browsing. Works with Claude Desktop, Claude Code, and any MCP-compatible client.

AI Banana Image Generator
Edit Images with Natural Language in 1-2 Seconds. Revolutionary Nano Banana AI technology delivers instant image editing and generation. Describe changes in plain English, preserve 95% identity accuracy, and create cohesive multi-image stories—all without traditional editing skills.

CodeConductor IDE Orchestrator gives Claude Desktop full access to your development environment through a secure MCP server. It connects Claude to your VS Code workspace, enabling real file operations, code navigation, Git workflows, and automated development tasks. The server exposes 24 IDE tools, including: File operations — open, read, write, list, search Code intelligence — go to definition, find references, diagnostics Git automation — status, diff, stage, commit, push (Pro) Command execution — run terminal commands safely (Pro) Command Execution Safety: Pro users can run commands through Claude, but everything is protected by a three-tier safety system. Safe commands run automatically, while higher-risk commands require explicit confirmation and are screened for dangerous patterns. This prevents accidental damage and blocks command injection attempts. All operations run locally on your machine, never transmit code, and follow a tier-based permission system (Free vs Pro). Requires the CodeConductor VS Code extension to function. This orchestrator turns Claude into a capable, controlled development assistant that operates directly inside your real project.

Prevents your AI from breaking code by revealing hidden file dependencies through git forensics.

A Model Context Protocol (MCP) server that provides secure SSH capabilities for AI assistants, enabling remote command execution, SFTP file transfers, and port forwarding with comprehensive security controls. Features: - 🔐 Secure SSH Command Execution - Execute commands on remote servers with granular security controls - 🛡️ Host Allowlisting - Only connect to pre-configured, trusted servers - 📁 SFTP File Operations - Upload, download, list, and delete files on remote servers - 🌉 SSH Port Forwarding - Create secure tunnels to access remote services - 🔄 Connection Pooling - Persistent connections with automatic management - 🔑 SSH Key Authentication - Secure authentication using SSH private keys - ⚙️ SSH Config Integration - Import servers from your existing SSJ config file - ✅ Command Allowlisting - Restrict which commands can be executed - 📦 Named Services - Pre-configured port forwarding services for common use cases - 🎯 Command Templates - Reusable parameterized commands with variable substitution

Create uncensored, high-quality, watermark-free AI images completely free and unlimited. Powered by the Flux.Dev open-source model, PictoFlux outputs HD results in ~5 seconds with up to 4 images generated in parallel so you can compare and pick the best. Choose from 25+ preset styles, multiple aspect ratios and high-res sizes, no registration required, with quality rivaling GPT-4o and other commercial models.

The GitHub MCP server provides comprehensive integration with GitHub, allowing you to manage repositories, create and review pull requests, handle issues, and interact with GitHub resources directly from your AI assistant.

Repo Context MCP provides programmatic access to repository contents for integrations and automation. It can list directories/files, read any file, return the README, perform TypeScript type analysis (via ts-morph), and search for OpenAPI/Swagger spec files. Supports local repo paths and reading from private GitHub repos when GITHUB_TOKEN is set in the environment. Ideal for code analysis, docs generation, and CI pipelines.

IssueBadge is a free online platform to create, issue, and share digital certificates and badges effortlessly. Perfect for schools, universities, nonprofits, businesses, and event organizers, you can bulk-generate certificates, add QR codes, and verify credentials instantly. Celebrate achievements with verifiable digital badges, boost recognition, and allow recipients to share certificates on LinkedIn, email, or websites. No design skills required. Start issuing today at https://issuebadge.com .

BrokerChooser’s MCP server provides a simple way for AI agents and applications to verify whether a financial entity, broker, or investment website is legitimate or potentially fraudulent. - Agents can check an entity by name or URL. - Results are powered by BrokerChooser’s aggregated scam database, which consolidates warnings and alerts from major financial regulators and official sources worldwide. - Developers can integrate this into applications to detect suspicious brokers, flag risks for end-users, and strengthen financial safety. In short: it’s a plug-and-play financial scam check API that helps prevent fraud.

BrokerChooser’s Scam Shield MCP server provides a simple way for AI agents and applications to verify whether a financial entity, broker, or investment website is legitimate or potentially fraudulent. - Agents can check an entity by name or URL. - Results are powered by BrokerChooser’s aggregated scam database, which consolidates warnings and alerts from major financial regulators and official sources worldwide. - Developers can integrate this into applications to detect suspicious brokers, flag risks for end-users, and strengthen financial safety. In short: it’s a plug-and-play financial scam check API that helps prevent fraud.

**Explore the I Ching with Quantum-Powered Reflection** Dive into the ancient wisdom of the I Ching, the 3,000-year-old Chinese *Book of Changes*, now enhanced with quantum random number generation. Generate true-random hexagrams for self-reflection, guided by AI-powered analysis combining classical interpretations, historical insights, and modern applications. Discover patterns, make decisions, and explore change with a tool that bridges ancient philosophy and cutting-edge technology.

**Explore the I Ching with Quantum-Powered Reflection** Dive into the ancient wisdom of the I Ching, the 3,000-year-old Chinese *Book of Changes*, now enhanced with quantum random number generation. Generate true-random hexagrams for self-reflection, guided by AI-powered analysis combining classical interpretations, historical insights, and modern applications. Discover patterns, make decisions, and explore change with a tool that bridges ancient philosophy and cutting-edge technology.

This MCP server exposes the Revel Digital REST API as tools that AI assistants can use to manage your digital signage infrastructure. Through natural language commands, you can: Manage devices, content, and playlists Monitor system status and performance Configure schedules and automation Access analytics and reporting data This enables conversational control of your digital signage network, making complex management tasks as simple as describing what you want to accomplish. More information here: https://www.reveldigital.com

Complete GitLab MCP integration with 72 specialized tools for comprehensive DevOps management

Generate conventional commit messages from your staged git changes using Model Context Protocol (MCP)

Provides context optimization tools to extract targeted information rather than processing large files and command outputs in their entirety.

Manage Gitea/Forgejo repositories through AI assistants.

GitHub MCP Server A Model Context Protocol (MCP) server that provides 29 Git operations + 11 workflow combinations for AI assistants and developers. This server exposes comprehensive Git repository management through a standardized interface, enabling AI models and developers to safely manage complex version control workflows. It is also a CLI tool as well.

this is a simple mcp server that helps user perform search in github

The GitBook MCP server enables programmatic access to GitBook Organizations, Spaces, Collections, and Content through a standardized MCP interface. It provides 12 tools for content operations and 6 AI-powered prompts for documentation workflows.

A Model Context Protocol server implementation for GitHub integration

增强版GitHub MCP Server，支持智能SSH访问检测和自动访问方式切换

DigitalOcean MCP Server for deploying and managing apps on App Platform

GitHub AI Agent powered by official GitHub MCP Server. Uses LangGraph and LangChain MCP Adapters. Agent is exposed on various agent transport protocols (AGNTCY Slim, Google A2A, MCP Server)

MCP wrapper for the `gh` command

MCP server for GitBook

Nova MCP servers collection - Puppeteer, GitHub, and Basic Memory integrations

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for GitHub (beta): https://www.cdata.com/download/download.aspx?sku=FGZK-V&type=beta

Repositório do projeto AI_ORBE criado via MCP GitHub Server para testes de automação.

🔍 A Model Context Protocol (MCP) server that provides semantic search capabilities for GitHub repository issues using FAISS and OpenAI embeddings. Perfect for developers who want to quickly find relevant issues, bug reports, and discussions across GitHub repositories using natural language queries.

A test repository created using the GitHub MCP server

Token-based GitHub automation management. No Docker for optimal performance, Flexible configuration for fine-grained control, 80+ tools with direct API integration. A comprehensive Model Context Protocol (MCP) server that enables your MCP client (Claude Desktop, Roo Code, Cline, Cursor, Windsurf, etc.) to interact with GitHub repositories using your GitHub personal access token. This tool simplifies managing GitHub repositories using only a GitHub token for setup. By skipping Docker, it avoids unnecessary complexity, delivering fast and effective results through direct API integration. This server is built using Node.js and provides a complete toolkit for repository management, issue tracking, collaboration management, and more, all while leveraging the GitHub API for optimal performance.

A repository for 2560_mcp. Includes instructions in README for enabling GitHub MCP server in VS Code.

A GitHub MCP server demo with create repository functionality

code or delegate aider over sse protocol

mcp coding tools over sse protocol

MCP (Model Context Protocol) client for GitHub Multi-User Server with Claude integration. Interactive chat interface for GitHub operations using natural language.

mcp git management server over sse protocol

A Model Context Protocol server implementation for GitHub

MCP server for working with GitHub repository via API.