MCP 服务器

Provides HTTP request capabilities through the Model Context Protocol. Enables AI agents to fetch web content, retrieve API responses, and download resources from URLs. Supports converting HTML to Markdown for easier consumption and can handle various content types including JSON, text, and binary data.

Provides a structured sequential thinking tool through the Model Context Protocol. Enables AI agents to break down complex problems into numbered thought steps, revise previous thoughts, branch into alternative paths, and adjust the total number of steps dynamically. Useful for multi-step reasoning, planning, and analysis tasks that benefit from explicit step-by-step thinking.

MCP server for Firecrawl's web scraping and crawling API. Converts any website into clean, LLM-ready markdown or structured data. Supports single page scraping, multi-page crawling with depth control, sitemap-based extraction, and batch operations. Handles JavaScript-rendered pages, bypasses common anti-bot measures, and returns structured content suitable for RAG pipelines and knowledge base construction.

Official MCP server for the Perplexity API Platform. Provides AI agents with real-time web search, deep research, and advanced reasoning capabilities through Sonar models. Includes tools for quick web search, conversational Q&A with citations, comprehensive deep research reports, and complex analytical reasoning. Returns answers with source attribution and supports configurable timeouts for long research queries.

MCP server for Todoist that lets AI agents create, update, complete, and query tasks using natural language. Supports projects, due dates, priorities, labels, and filters, making it easy to manage a personal or team task list conversationally.

MCP server for Intercom. Lets AI agents search and read conversations and contacts, retrieve message history, and query help-center articles via the Intercom API. Useful for support analytics, conversation summarization, and building assistants that reason over customer communications.

An MCP server that lets AI assistants delegate work to the Google Gemini CLI, taking advantage of Gemini's very large context window for whole-file and codebase analysis. Exposes tools to ask Gemini questions with file references, brainstorm ideas, and stream long responses in chunks, so a client model can offload large-context reasoning to Gemini without leaving the current session.

JFrog's MCP server lets agents work with Platform services for artifact repositories, build information, release lifecycle management, and software supply-chain workflows.

Octopus Deploy's official MCP server helps agents inspect, query, and diagnose deployment infrastructure, projects, releases, and environments.

Sanity's official MCP server that connects structured content to AI agents. Provides tools to run GROQ queries, read and write documents, explore and deploy schemas, manage content releases, and generate images, all with full schema context. Available as a hosted remote server at mcp.sanity.io and works with MCP-compatible clients like Cursor, Claude Code, and VS Code.