Tradovate MCP Server

Run personalised outreach campaigns and manage conversations using a virtual computer equipped with email capabilities, research tools, and workflow automation. Email Outreach by OpenHelm enables your agent to carry out work such as: • Prospect research • Personalised outbound email campaigns • Lead qualification • Follow-up sequences • Inbox monitoring and response handling What makes OpenHelm the best solution for this: • AI continuously monitors conversations and adjusts actions to maximise outcomes • Deep research capabilities enable highly personalised outreach at scale • Multi-step workflows coordinate research, sending, follow-ups, and response management • Operates within a secure remote environment isolated from your local machine For organisations looking to generate opportunities through outbound communication, OpenHelm provides the infrastructure needed to run sophisticated outreach workflows autonomously.

GitLab API, enabling project management

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

Zhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.

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

MCP server for freshjots.com

Retrieving and analyzing issues from Sentry.io

MCP server for StillOnline — uptime monitoring and status pages from Cursor, Claude Code, and other MCP clients. Wraps REST API v1: projects, HTTP/SSL checks, incidents. Requires Pro/Ultimate API key.

Local-first, lightweight MCP server for per-agent key management.

Structured business info (address, hours, services, payment methods, languages, insurance) for any named business — combines OpenStreetMap + KVK Handelsregister + LLM-extracted website data.

HelloGrowth CRM MCP is an AI-powered CRM integration platform that enables secure AI access to CRM data, lead and customer management, deal tracking, task automation, and business workflow orchestration through a standardized MCP interface.

Web content fetching and conversion for efficient LLM usage

Bikefuchs is a price-comparison and basket-optimization tool for bicycle parts, components and apparel across German and Austrian online shops. Give it one or more products and it finds the same item across shops, checks availability, and computes the cheapest way to split your basket — including each shop's shipping costs.

Recruiting-ops MCP for asking Factorial ATS questions and finding bottleneck owners inside Claude, Cursor, or another AI workspace.

A Model Context Protocol server bridging LLM agents to the Prolific public API. Built with FastMCP. Listed on the official MCP Registry — discoverable from Claude Desktop, Cursor, Claude Code, and other MCP-aware clients. Exposes a small set of tools so an LLM can help a researcher design and launch a study on Prolific.

# 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)

Recruiting-ops MCP for asking TalentLyft questions and finding bottleneck owners inside Claude, Cursor, or another AI workspace.

Read-only database access with schema inspection

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

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

AgentDrive is a cross-agent artifact workspace with provenance and portable storage across Claude Code, Codex, Cursor, and LangGraph. 20 MCP tools: file CRUD, semantic recall over workspace artifacts, run logging, cross-agent attribution, comments, and shares. Connect to the hosted server at https://mcp.agentdrive.sh/mcp with an Authorization: Bearer key, or run locally via npx @adrive/mcp-server. Free tier (1 GB + 10k embeddings) at https://app.agentdrive.sh — no credit card.

Conduct comprehensive research projects using a virtual computer equipped with a real browser, coding tools, document creation capabilities, and more. Deep Research by Openhelm enables your agent to tackle work such as: • Market and competitor analysis • Industry and company research • Investment and acquisition due diligence • Technical and scientific investigations • Report generation with sources and evidence What makes OpenHelm the best solution for this: • Research is continuously reviewed and refined by a powerful AI to maximise accuracy and completeness • Uses a highly capable stealth browser that can access more of the web than traditional research agents • Multi-step workflows allow findings to be validated, expanded, and synthesised automatically • Generates structured outputs rather than simply returning search results For high-stakes research that requires depth, accuracy, and persistence, OpenHelm provides a secure remote environment where complex investigations can be completed autonomously.

Location services, directions, and place details

Create a remote sandbox that can execute code/run commands/upload and download files. 创建远程沙盒，可以执行代码/运行命令/上传下载文件

Turn any published podcast into clean Markdown with real speaker names — not "Speaker 1." Three tools: search_podcasts (by text query or a pasted Spotify/YouTube URL), get_transcript (named, timestamped Markdown ready for LLMs and RAG), and get_balance. It's a transcript-retrieval API, not speech-to-text: it works on already-published shows, so you skip uploading audio and diarization — typically 5–10× cheaper. Try it free with the demo key pt_demo (no signup).

虎嗅嗅官方AI助手，可查询AI行业早报、投融资事件、产品动态、硬件与原生关键信号。

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