Sql Server Mcp

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Serveur MCP HACCP francophone — réglementation sanitaire française pour restaurants, boulangeries, boucheries et métiers de bouche. Températures réglementaires, DLC, allergènes, rappels produits RappelConso, sanctions DDPP, score Alim'confiance, actions correctives et comparatif solutions.

Generate n8n workflow JSON (including LangChain AI agents), scaffold custom TypeScript nodes, and lint workflows for missing credentials, deprecated types, and broken connections.

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

Search and retrieve public procurement tenders for Norway, Sweden, Denmark, Finland and Iceland (sourced from TED), plus the full Norwegian company registry. Built for AI agents — every tool returns clean JSON with stable IDs. Authenticate with an API key in the X-API-Key header. Free plan available, no credit card required. search_tenders — Search Nordic procurement notices by country, keyword, CPV code, or date range get_tender — Fetch a single tender by ID search_companies — Search the Norwegian company registry get_company — Fetch a single Norwegian company by org number Transport Streamable HTTP (not stdio, not SSE) Auth Header X-API-Key: <your_key> — get one free at https://nordicdata.cloud

The match graph for AI. Search 100,000+ capabilities across 13,000+ AI artifacts — models, agents, MCP servers, APIs, frameworks, CLIs, and more. Every query learns from the graph, making the next search smarter. 10 tools: search, find_mcps, get_artifact, compare, find_stack, resolve_capability, trust_passport, feedback, subscribe, unsubscribe. Install: npx -y @unfragile/mcp-server

The simplest, most complete, end-to-end agent-managed company brain. One workspace where humans and any MCP-compatible AI agent (Claude, Cursor, Windsurf, ChatGPT, Gemini, and more) co-author living documents (Markdown-native with a rich superset on top), 40+ visual diagrams (Mermaid, BPMN 2.0, D2, PlantUML, GraphViz, ELK, Excalidraw freehand), plans, timelines, tasks, improvements, and a self-learning Knowledge Graph that IS the company brain. Lean, fast, secure, and affordable — flexible enough for one person organising a personal mind, through to small businesses, growing businesses, and enterprise. 163 MCP tools across 16 categories let an agent drive end-to-end: sign-up → billing → org/workspace/project → members → teams → permissions → brain scope → docs → diagrams → plans, all without a human touching the UI. Auth: OAuth 2.1 with Dynamic Client Registration, or Bearer API key with prefix sta_. Public repo: https://github.com/stablebaseline/mcp · Docs: https://stablebaseline.io/docs/mcp

Automatically create a remote browser to complete your specified tasks, developed based on Browser Use + Sandbox. 自动创建一个远程浏览器，完成你指定的任务，基于Browser Use + Sandbox开发。

Verify AI agent tool calls with content-addressed, HMAC-attested receipts. Free third-party verification API for AI agents. Call verify_action(claim, evidence) to get an independent integrity check on whether your claimed action matches the actual evidence. Useful for catching silent failures: incorrect SQL operations, file-op mismatches, API call inconsistencies, and code-diff scope creep. Five specialized verifier kinds: - code_diff: verb / path / identifier coherence with unified diff - db_op: row delta + SQL operation + ID match - file_op: existence state + line/size delta - api_call: request body and response status coherence - generic: conservative fallback Returns: - aar_verdict: verified | contradicted | insufficient_evidence | unsafe_to_verify - verdict: ok | mismatch | uncertain (legacy 3-value alias) - reasoning, confidence - receipt: verify_action_receipt.v0 with HMAC-SHA256 signature, content-addressed via SHA-256 hashes of claim and evidence Cross-vendor: works with Claude Code, Cursor, Cline, Codex, Codeium, and any MCP-compatible harness. Stateless, per-request, no API key, no registration. Pure Python stdlib (no pip install). Anonymized telemetry only — no PII, no model fingerprint, no raw claim/evidence retention. Honest scope: this is a small reference implementation, not a canonical inter-vendor standard. v0 receipts use HMAC-SHA256 (symmetric, single-issuer); v1 with ed25519 + multi-issuer is on the roadmap. The hosted endpoint has no SLA — self-host for stability (git clone && ./start.sh). 90-day probe with explicit kill criteria. If adoption appears, v1 schema work begins. If response is null, the null is itself a publishable data point.

Architecture Diagrams Built and Maintained by AI

The first payment-contingent FX protection server on MCP. Price a Guard (invoice-linked FX protection for SME invoices and payables), get live spot and forward rates, model 25 years of historic FX stress scenarios, and resolve settlement dates — all via natural conversation. Public endpoint, no authentication required. Designed for PSPs, accounting platforms, and agentic cross-border payment workflows.

grpc-invoke-mcp is an MCP server for calling gRPC methods from AI agents like Claude Code, Codex, Cursor, and other MCP-compatible tools. It gives agents a simple way to inspect gRPC APIs and invoke unary RPCs using either server reflection or local .proto files. This is useful when you want an agent to explore services, understand request and response schemas, make real gRPC calls, and test gRPC integrations during agent-driven development without writing one-off scripts.

Ask your AI agent why your tests are failing. Instant analysis on failures and regressions.

Torify gives AI agents the Japanese locale primitives that standard libraries lack — imperial era date conversion (wareki), qualified invoice number validation with NTA registry lookup, corporate number lookup (法人番号), postal code resolution, name romanization (Hepburn), and kanji-to-kana conversion via Yahoo! JLP. 31 endpoints total. No authentication required for MCP. Pay-per-call $0.02/call via x402 USDC on Base, or $49/mo Pro subscription.

基于Anduin2017 / HowToCook （程序员在家做饭指南）的mcp server，帮你推荐菜谱、规划膳食，解决“今天吃什么“的世纪难题； Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"

A Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.

*One workspace for your prompts, documents, and collections — accessible from every AI client you use.* Context Repo is an AI context management platform for capturing, organizing, versioning, and searching the knowledge artifacts you use with AI tools. This MCP server exposes **28 tools** that give Claude, Cursor, ChatGPT, Factory, Windsurf, Codex, Claude Code, and any other MCP-compatible client direct read-and-write access to your personal workspace — no copy-paste, no context loss between conversations. ## Features - **Prompts** — Full CRUD with version history, rollback, and semantic search across your prompt library - **Documents** — Markdown and plain-text storage with automatic chunking and 1536-dim vector embeddings - **Collections** — Named folders that group prompts and documents into project-scoped contexts - **Catalog Search** — `find_items` returns ranked results across prompts, documents, and collections in a single call (semantic by default, literal fallback) - **Deep Search** — Hierarchical document navigation: search ranked passages, then expand up to parents, down to children, or sideways to siblings for token-efficient exploration of long content - **Version History** — Every content edit creates a new version; restore any prompt or document to any previous state - **Real-time Sync** — Changes propagate instantly via Convex live queries; AI clients always see the latest content - **ChatGPT Apps Ready** — `search` and `fetch` are OpenAI Apps SDK Company-Knowledge eligible; `find_items` carries an optional `ui://` resource for inline result rendering ## Tools (28 total) | Category | Tools | |---|---| | User Info (1) | `get_user_info` | | Prompts (7) | `search_prompts` · `read_prompt` · `create_prompt` · `update_prompt` · `delete_prompt` · `get_prompt_versions` · `restore_prompt_version` | | Documents (7) | `list_documents` · `get_document` · `create_document` · `update_document` · `delete_document` · `get_document_versions` · `restore_document_version` | | Collections (7) | `list_collections` · `get_collection` · `create_collection` · `update_collection` · `delete_collection` · `add_to_collection` · `remove_from_collection` | | Catalog (1) | `find_items` | | Deep Search (3) | `deep_search` · `deep_read` · `deep_expand` | | ChatGPT Apps (2) | `search` · `fetch` | ## Authentication Two ways to connect: 1. **API Key** — Generate a scoped `gm_*` key at [contextrepo.com/dashboard/settings](https://contextrepo.com/dashboard/settings). Per-key permissions: `prompts.read`, `prompts.write`, `documents.read`, `documents.write`, `documents.scrape`. Sent as `Authorization: Bearer gm_...`. 2. **Clerk OAuth 2.0** — RFC 9728 protected-resource metadata at `/.well-known/oauth-protected-resource/mcp`, RFC 8414 authorization-server metadata at `/.well-known/oauth-authorization-server`. Standard OAuth flow for clients that support it. ## Use Cases - **Prompt library that follows you.** Stop copy-pasting prompts between Claude, Cursor, and ChatGPT. Maintain one canonical version, retrieve it from any client. - **Personal knowledge base.** Save research articles, documentation, and AI conversations with the [Context Repo Chrome Extension](https://contextrepo.com/chrome-extension), then pull them in as grounded context inside your AI tools. - **Project-scoped collections.** Separate workspaces per client, repo, or topic so an AI assistant only sees what's relevant to the task at hand. - **Version-controlled prompts.** Track how prompts evolve, A/B test variants, and roll back when an "improvement" turns out worse. - **Long-document exploration.** Deep Search navigates book-length documents passage by passage instead of dumping them into context — every chunk carries parent/child/sibling links the agent can walk. ## Compatibility Streamable HTTP transport, MCP spec ≥ 2025-03-26. Verified with Claude Desktop, Cursor, ChatGPT (via the OpenAI Apps SDK), Factory, Windsurf, Codex, Claude Code, VS Code (Continue), and Amp. Any MCP-compatible client should work. ## Resources - Website: [contextrepo.com](https://contextrepo.com) - Documentation: [contextrepo.com/docs](https://contextrepo.com/docs) - Pricing & free trial: [contextrepo.com/pricing](https://contextrepo.com/pricing) - Agent discovery: [contextrepo.com/llms.txt](https://contextrepo.com/llms.txt) - API reference: [contextrepo.com/openapi.json](https://contextrepo.com/openapi.json)

62 real-time data tools for AI agents via MCP. Finance, crypto, FMCSA, property, weather, vehicles, sanctions screening (OFAC/EU/UN/BIS), FEMA disasters, federal courts, cybersecurity, US college metrics. One bearer token, one bill. Free tier available.

FullMt5McpByLeo is a complete, production-ready MCP server that enables Claude and other AI assistants to control MetaTrader 5 directly. Execute trades, retrieve market data, manage charts, analyze trading history, and automate MT5 operations through natural language.

Location services, directions, and place details

The internet's largest queryable infrastructure graph — 7.39 billion nodes, 39 billion edges, 5.6 million threat-intelligence relationships. Pivot from any IP, domain, or ASN across DNS, BGP, WHOIS, GeoIP, and threat intel in a single Cypher query. Most threat-intel and OSINT APIs are point lookups: you ask about one indicator, you get one record. Investigations don't work that way — you start from one suspicious domain and need to trace its hosting, its sibling domains, its registrar, its email infrastructure, the ASN announcing its IP, and which feeds have flagged anything nearby. WhisperGraph stores all of that as a single connected graph and lets you traverse it natively. One query can answer questions that would take dozens of API calls anywhere else. Example questions you can ask **Is xyz-uknown@suspicious.com a safe email address? **What is the IP address of whisper.security? "What's the threat reputation of 45.142.213.55, and what feeds flagged it?" "Show every domain sharing this domain's MX records and registrant email." "Map the full DNS and BGP attack surface of example.com." "Which ASNs in Russia have the highest concentration of phishing-flagged IPs this quarter?" "Find all domains registered within 24 hours of suspicious-domain.com using the same registrar." "What's the historical WHOIS for disputed-domain.com going back 5 years?" "Which prefixes does AS13335 currently announce, and were any of them previously announced by a different ASN?"

Channel management and messaging capabilities

Branded chart rendering for AI agents — hosted MCP server, zero setup

Official MCP server for 100Hires ATS: candidates, jobs, applications, interviews, messages.

MCP Advisor & Installation - Use the right MCP server for your needs

An MCP server and REST API that classifies Polymarket wallets as human or bot, scores their trading edge from 0–10, and streams their current open positions. Built for AI agents on copy-trading and signal-following stacks. # Use it from any MCP client (Claude Desktop, Cursor, etc.) pip install polymarket-intel-mcp polymarket-intel-mcp # Or call the hosted REST API directly curl https://polymarket-intel-production.up.railway.app/wallet/0xf1528f12e645462c344799b62b1b421a6a4c64aa How this fits with other Polymarket MCP servers There are several MCP servers covering Polymarket, each at a different layer: Server What it does When to use it polymarket-intel (this) Wallet intelligence — classify human vs bot, score trading edge, read open positions Deciding whose signals to follow graph-polymarket-mcp Market data via The Graph subgraphs (20 tools, 8 subgraphs) Reading raw on-chain market data whitmorelabs/polymarket-mcp Slippage, liquidity, arbitrage, price feeds Pricing your own trades joinQuantish/polymarket Self-hosted trading agent Running an autonomous bot These complement each other. A copy-trading agent would use polymarket-intel to filter wallets worth following, then graph-polymarket-mcp to read the markets those wallets are betting on, then whitmorelabs/polymarket-mcp to size its own entries. What it answers "Is this trader a human or a bot?" — score_polymarket_wallet(wallet_address) → returns classification ∈ {human, bot, insufficient_data} plus a confidence score and reason codes. "Do they actually have an edge?" — edge_score from 0–10, gated on net realised PnL so distributed-but-losing wallets don't get false positives. "What are they betting on right now?" — get_open_positions(wallet_address) returns live positions sorted by size, refreshed every 30s. "How has their edge changed over time?" — /wallet/{address}/history returns the score time series from the daily snapshots. Why this exists The Polymarket leaderboard is misleading. It includes unrealised PnL marked-to-current-price, so the names at the top are dominated by bots running structural arb plus a few wallets sitting on huge open positions that may never resolve in their favour. Agents that copy-trade naively from the leaderboard get burned. This service runs every leaderboard wallet through behavioural fingerprinting (focus ratio, holding period, timing regularity, category concentration) plus PnL reconstruction from raw activity, and only surfaces traders that look like genuine humans with a real edge. The dataset grows more valuable over time — every day the snapshot job runs, historical signals accumulate. Wallets that have been consistently above edge 7 for 90 days are a stronger signal than any single point-in-time score. Distributed as both a REST API and an MCP server Surface Use case Setup MCP server Agent that needs tool-style access pip install polymarket-intel-mcp REST API Custom HTTP integration, dashboards curl https://polymarket-intel-production.up.railway.app/... Hosted MCP Agent on any MCP-compatible client Add https://polymarket-intel-production.up.railway.app/mcp to client config Architecture ┌──────────────────────────────────────────────┐ │ core/ │ │ client.py — Polymarket data API client │ │ signals.py — pure signal calculators │ │ scorer.py — classifier + edge score │ │ models.py — Pydantic response schemas │ ├──────────────────────────────────────────────┤ │ db/ │ │ schema.sql — Postgres tables + indexes │ │ repository.py — Repository protocol + │ │ InMemoryRepository │ │ supabase_repo.py — Supabase impl │ │ converters.py — ScoreResult ↔ records │ ├──────────────────────────────────────────────┤ │ api/main.py — FastAPI HTTP server │ │ mcp_server/ — MCP server (stdio) │ │ scripts/ │ │ analyze_wallet.py — CLI │ │ snapshot_job.py — daily cron entry │ │ tests/ │ └──────────────────────────────────────────────┘ Core has no idea persistence exists. The API and snapshot job depend on the Repository protocol — Supabase in production, in-memory in tests and when env vars are unset. This is what makes the suite run without a database and what lets you swap Supabase for Neon, RDS, or anything else later by adding one file.

MCP server for interacting with Neon Management API and databases