IMCP – Apple iMessage, Reminders, Calendar, Contacts and more

Web and local search using Brave's Search API

Crawlora's hosted MCP server exposes 319 structured web-data tools — search, maps, commerce, social, finance, travel, app stores, and reviews — each returning clean JSON instead of HTML to parse. Streamable HTTP transport with API-key Bearer auth. No proxies, browsers, or parsers to maintain. Free 2,000 credits/month, no card.

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.

RollingGo-Flight-MCP is a native MCP plugin for global air ticketing services. Powered by the world’s 3rd largest travel B2B firm. Totally free with no call quota limits. Fully compatible with AI Agents including Claude, Cursor, Codex and mainstream MCP clients. It aggregates 500 airlines, covering flight routes across 200 countries and regions.

Kage is shared, code-grounded memory for developers and their coding agents. Capture a learning once — a bug cause, a decision, a gotcha — and the whole team plus every agent recalls it next time it's relevant. Memory is grounded in your actual code and stored as git-tracked JSON reviewed in PRs, not a personal vector blob that drifts: citations are validated on write, and stale memory (whose code was deleted or refactored) is withheld from recall and flagged for you. Works with Claude Code, Codex, Cursor, Windsurf, and any MCP client. No vector DB, API key, or service to run. Try it in 30s: npx -y @kage-core/kage-graph-mcp demo

AI Governance Infrastructure for Microsoft 365. 24 MCP tools with policy enforcement, Need-to-Know compliance filter, revision-safe audit trail, and per-resource scope control. Deployed in your own Azure tenant — your data never leaves. DSGVO-first, EU AI Act ready.

clariBI is an AI-powered business intelligence platform built for small and mid-sized SaaS, ecommerce, and operations teams. Instead of writing SQL or building dashboards manually, users ask questions in plain English ("what's our CAC by channel last quarter?") and the AI engine pulls the data from Stripe, HubSpot, Google Analytics, ad platforms, Jira, and 30+ other sources via the open Model Context Protocol. Dashboards generate themselves on source connect.

mneme is an open-source, vault-native memory layer for Claude Code and any MCP client. Your Markdown files are the source of truth. The index, embeddings, and knowledge graph are all derived and rebuildable. No LLM or network on the capture path. Redaction runs before every derived store. MIT licensed.

Truee is a platform that helps businesses create a trusted, AI-ready business profile so AI systems, search engines, agents, and customers can understand exactly who they are, what they do, where they operate, and how to contact them. Instead of AI guessing or using outdated public information, Truee lets businesses control and update their own structured business data. A simple way to say it: Truee helps businesses tell AI the truth about them. Or: Truee is a trusted business data layer for the AI-first internet. It helps businesses with: Accurate business information AI discoverability Structured business profiles Trust and verification Updates for services, location, contact details, announcements, and offers Better visibility when AI agents are searching for businesses to recommend For customers and AI systems, Truee becomes a reliable source of business information. For businesses, it means: One Truee profile, thousands of AI agents can understand and find you when your business is needed.

The Meteomatics MCP (Model Context Protocol) server allows AI agents to securely access Meteomatics weather data tools. MCP is an open standard that lets AI applications connect to external tools and data sources. With the Meteomatics MCP, agents can request weather data directly from the Meteomatics API through a secure /mcp endpoint. The MCP server manages authentication using OAuth (client registration, authorization code + PKCE, and refresh tokens). Once connected, the AI agent can access data, models, parameters, time ranges that are available to your Meteomatics API account.

An MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.

# 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)

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).

A Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.

MCP server to provide Figma layout information to AI coding agents like Cursor

GitLab API, enabling project management

Bitly is the world's most trusted link management platform - and now your AI assistant can tap directly into everything it tracks. With the Bitly MCP Server, you can pull real-time engagement data on any link, QR code, or page: click volume, top locations, referral sources, device breakdowns, and performance over time. Ask your AI to surface your top-performing links this week, flag anything with unusual click patterns, or compare campaign performance across channels - all in natural conversation. Once you have the data, creation is just as seamless. Generate branded short links with custom domains and UTM parameters, produce print-ready QR codes with your brand colors and logo - all without leaving your workflow. 27 tools. Full Bitly platform access. Works with Claude, ChatGPT, Cursor, VS Code, and Windsurf.

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

Hand any AI agent a budget-capped wallet to pay, discover & register x402 payment-gated URLs across every chain. Local, self-custodial, no backend, no fee.

Model Context Protocol server that integrates AgentQL's data extraction capabilities.