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Spf Smart Gate rust binary mcp server with built in local tools. preconfigured
@joseph stone

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.*

15 days ago
Memtrace
@syncable-dev

Memtrace — Structural Memory for AI Coding Agents The Problem Every AI coding agent — Claude Code, Cursor, Codex, Copilot — starts each turn completely blank. It re-reads raw source files and re-derives the full call graph, type hierarchy, and import tree from scratch on every single invocation. That structural rework burns 60–90% of the context window before any real reasoning begins. Less than 5% of tokens in a typical agentic coding session contribute genuine new intelligence. The rest is expensive, redundant noise — and it compounds: accuracy drops 40% as sessions grow, stale context crowds out signal, and summaries strip out the structural relationships agents need most. The Solution Memtrace is a bi-temporal structural memory layer that turns your codebase into a live, queryable knowledge graph — compiled from the AST, not guessed from embeddings. Every function, class, interface, and API endpoint becomes a typed node with deterministic relationships. Every file save becomes a queryable episode with timestamps, so agents can reason about structure, detect regressions, and time-travel through their own work without re-reading anything. One Rust binary. Zero configuration. Five-minute install. What agents can do with it Find callers, callees, and dependencies instantly — no file scanning, no token waste Compute blast radius before making a change — know exactly what breaks before anything is touched Detect structural drift between sessions — catch regressions the moment they happen, not at PR review Time-travel through code evolution — query any prior state of any symbol, not just git commits Search across the full codebase with hybrid retrieval — BM25 full-text + HNSW vector + graph traversal fused in one query Map API topology across services — cross-repo HTTP call graphs, dependency chains, dead endpoint detection Benefits −90% token cost on structural queries (Mem0) +26% accuracy on multi-step agentic tasks (Mem0) −91% p95 latency on structural lookups vs. RAG baselines +32.8% SWE-bench bug-fix success rate when agents have graph context (RepoGraph) 200–800ms per-save re-indexing — every file save is a queryable episode in under a second 40+ MCP tools covering indexing, search, relationships, impact analysis, temporal evolution, API topology, graph algorithms, and direct Cypher queries 12 languages + 3 IaC formats supported via Tree-sitter grammars Local-first, closed-source Rust — code never leaves the machine, no account required, no telemetry

a month ago
Wundertrading Mcp Server
@WunderTrading

WunderTrading MCP connects AI agents and coding tools to live crypto trading execution through WunderTrading. It gives agents a way to turn trading decisions into real actions on connected exchanges using WunderTrading as the execution layer via MCP or REST API. WunderTrading’s docs describe MCP setup through a dedicated server endpoint with HMAC API credentials. The platform positions this MCP integration for broader AI trading workflows, not just basic order placement. AI agents can combine strategy instructions with market data, technical signals, news, sentiment, screenshots, and other inputs, then place and manage trades automatically on connected exchanges. WunderTrading highlights use cases such as pattern-recognition trading, sentiment-based trading, copy trading automation, portfolio rebalancing, cross-exchange arbitrage, trade history analysis, backtesting, signal automation, and order book trading. WunderTrading highlights support for 20+ exchanges and shows leading supported venues including Binance, Bybit, Coinbase, Bitget, OKX, KuCoin, Hyperliquid, and BingX. Its supported exchanges page also describes WunderTrading as a multi-exchange crypto trading platform with a single interface and secure API access. Setup is straightforward: create a WunderTrading account, generate HMAC API keys, add the wundertrading MCP server to your MCP client configuration, and connect your exchange accounts so the agent can execute trades. WunderTrading says live trading through MCP/API is available from the PRO plan, while paper trading is available for testing.

a month ago