MCP example Netlify Express

Deterministic tools for AI agents. More reliable than AI inference. A lightweight utility API suite for developers and AI agents.

MCP server for freshjots.com

bugAgent turns your AI assistant into a full QA engineer. Create and triage bug reports with AI root-cause analysis, manage test cases and runs, write and execute Playwright automations, run security and performance scans, and track team quality metrics — all from Claude, Cursor, or any MCP client. 109 tools covering the full QA lifecycle. Requires a free bugAgent account at app.bugagent.com.

A stdio MCP server that connects MCP-compatible Agents to Redis for safe key/value, hash, list, set, metadata, and diagnostic operations. Part of MCP Java SDK, a Java toolkit for building custom MCP Servers.

B2B enrichment API for AI agents — 89 canonical fields per person + company, each annotated with source, confidence (0-1) and freshness. One call synthesises ten sources; no per-field bills. Add https://mcp.abm.dev/mcp as a custom MCP connector (OAuth 2.1 PKCE).

European AI orchestration platform — connects CRM, ERP, documents with LLMs. GDPR-compliant, EU-hosted, MCP-native. 4 tools: search_documents, query_database, create_record, send_notification.

Personal CRM for your AI assistant — search contacts, manage notes and tags, sync Google and Microsoft calendars, import LinkedIn connections, and bulk import contacts.

MCP server for the Savvly Longevity Benefit Fund: product info, Savvly-vs-alternative comparisons, eligibility checks, an audience-tagged Q&A library, and retirement / lump-sum / monthly projections (with inline MCP Apps chart widgets).

GraphPilot gives coding agents persistent structural knowledge of a codebase. It parses TypeScript/JavaScript with tree-sitter into a graph of symbols and call edges, then exposes that graph over MCP so the agent can recall definitions, find callers, and trace change impact without re-reading files every conversation. Local-first: no network, no telemetry, no code ever leaves your machine. Four tools — gp_index, gp_recall, gp_callers, gp_impact.

Multi-perspective decision reasoning for Claude. When you face a real choice: career, money, relationships, strategy. Orlog examines competing angles and takes a clear position, not a hedge. Get an API key at orlog.fyi.

Location services, directions, and place details

Synx is an AI first board for projects and tasks. It enhances your agentic workflow by helping the AI (and the human) manage the development process from start to finish.

51 AI-powered Intelligence verticals - finance, immigration, legal, health, crypto, real estate, careers, travel, compliance and more. x402-native, pay-per-query via USDC on Base. No API keys, no subscriptions.

AI image generation using various models

Flag features directly from chat in your code editor, including VS Code, Cursor, Windsurf, Claude Code—any IDE with MCP support.

Mercury is a pay-per-call MCP server that lets AI agents discover and call financial data tools using the x402 HTTP payment protocol. 18 tools covering crypto prices, DeFi liquidity, NFT data, on-chain analytics, and more. tools/list is free — tools/call is billed per call using your Mercury API key. Connect by URL: https://network.mercury-hq.com/mcp

# govql-mcp-server An MCP (Model Context Protocol) server for [GovQL](https://govql.us) — gives AI clients like Claude Desktop, Claude Code, and Cursor direct access to the US Congressional GraphQL API at [api.govql.us/graphql](https://api.govql.us/graphql) without bespoke HTTP wiring. For the design rationale (why FastMCP-Python, the passthrough+curated philosophy, roadmap through v0.4), see [design.md](https://github.com/govql/govql/blob/main/mcp-server/docs/design.md). ## What you can do with it Ask an agent questions like: - *"How did Vermont's two senators vote on the most recent nomination?"* - *"Which legislators in the 118th Congress switched parties during their service?"* - *"Compare Senator Sanders' voting record to Senator Murkowski's on cloture votes in the most recent Congress."* The agent picks the right tool, writes the GraphQL query against the live schema, and parses the response — no manual API wrangling. ## Install The server runs as a per-client subprocess over stdio. Pick your client: ### Claude Desktop Edit `claude_desktop_config.json` (Settings → Developer → Edit Config): ```json { "mcpServers": { "govql": { "command": "uvx", "args": ["govql-mcp-server"] } } } ``` Restart Claude Desktop. The `govql` tools appear in the tools panel. ### Claude Code Add to `.mcp.json` in your project (or `~/.mcp.json` for global): ```json { "mcpServers": { "govql": { "command": "uvx", "args": ["govql-mcp-server"] } } } ``` ### Cursor Settings → MCP → Add Server. Use the same `command` / `args` as above. ### Other clients Any MCP-compatible client that supports stdio servers will work. The command is `uvx govql-mcp-server` with no required arguments. ## Tools | Tool | Purpose | |---|---| | `execute_graphql` | Run any GraphQL query against the GovQL endpoint. Returns the result plus an `last_ingest` timestamp so the agent can reason about data freshness. | | `list_types` | Returns the names and kinds of every type in the GovQL schema. Optional `kind` filter (`"OBJECT"`, `"INPUT_OBJECT"`, `"ENUM"`, etc.) to narrow further. Start here when you don't know what's queryable. | | `describe_type` | Returns one type's full details — fields, arg signatures, input fields, enum values. Call after `list_types` to learn the shape of a specific type before writing a query. | ## Configuration All env vars are optional — the package is zero-config for end users. | Env var | Default | Purpose | |---|---|---| | `GOVQL_ENDPOINT` | `https://api.govql.us/graphql` | Endpoint to query. Override to point at a local dev stack. | | `GOVQL_TIMEOUT_MS` | `30000` | Per-request HTTP timeout. | | `LOG_LEVEL` | `INFO` | Logging level. Logs go to stderr only (stdout is reserved for the MCP transport). | ## Limits (enforced by the upstream API) - Max query depth: 10 - Max query complexity: ~10 billion points (`first: N` multiplies child cost by N — keep page sizes reasonable on deeply nested queries) - Rate limit: 100 requests / 60 s per source IP A depth or complexity violation surfaces as a GraphQL `errors` entry in the tool response so the agent can adjust and retry. ## Data freshness Every `execute_graphql` response includes a `last_ingest` ISO timestamp. Vote data refreshes hourly; legislator data refreshes daily. ## Status Version 0.1.0 ships three foundational tools: a GraphQL passthrough (`execute_graphql`) and two narrow schema-discovery tools (`list_types`, `describe_type`). Curated higher-level tools (`find_legislator`, `get_voting_record`, `compare_voters`, etc.) are planned for subsequent releases — see [design.md](https://github.com/govql/govql/blob/main/mcp-server/docs/design.md) for the roadmap. ## Links - [GovQL project site](https://govql.us) - [GraphQL API](https://api.govql.us/graphql) - [Source / issues](https://github.com/govql/govql)