MCP 服务器
开放的 Model Context Protocol 服务器注册表。按类别、传输方式或使用场景,为 AI 智能体寻找合适的工具、资源和提示词。
服务器
177
工具
471
类别
11
贡献者
155
Official Hugging Face MCP Server that connects AI assistants directly to the Hugging Face Hub ecosystem. Provides tools for searching and retrieving models, datasets, and research papers, running inference on thousands of Gradio-powered AI applications (Spaces), and accessing the full Hub API. Supports remote HTTP-streaming via https://huggingface.co/mcp with OAuth or Bearer token auth, as well as local stdio deployment. Works with Claude, Gemini CLI, VS Code, Cursor, and any MCP-compatible client.
Official Cloudflare MCP server for managing Cloudflare services. Enables AI agents to interact with Workers, KV namespaces, R2 storage, D1 databases, and DNS records. Supports deploying Workers scripts, managing environment variables, querying analytics, and configuring security settings across Cloudflare's edge network.
MCP server for Atlassian Confluence that lets AI agents search the knowledge base, read and create pages, update content, and navigate spaces. Useful for grounding answers in internal documentation and for drafting or maintaining wiki content directly from an AI client.
MCP server for the ClickUp project management platform. Enables AI agents to create and update tasks, browse spaces, folders, and lists, and manage task status and assignees, bringing ClickUp work management into AI-powered tools.
Official DigitalOcean MCP server for managing cloud infrastructure. Lets AI agents deploy and manage App Platform apps, Droplets, databases, and Spaces object storage, and read logs and metrics. Useful for provisioning and operating cloud resources and debugging deployments through an AI assistant.
Provides access to the Slack API through the Model Context Protocol. Enables AI agents to read and send messages, manage channels, search conversation history, and interact with Slack workspaces. Supports listing channels, reading threads, posting messages, and adding reactions programmatically. Originally maintained by Anthropic, now maintained by Zencoder.
Contentful's official MCP server for the Content Management API. Gives AI agents tools to create, edit, organize, and publish content, manage content models and assets, and work across spaces and environments. Useful for automating editorial workflows and content operations in a Contentful-backed headless CMS.
Postman's official MCP server that connects the Postman platform to AI tools. Gives agents the ability to access workspaces, manage collections and environments, work with API specifications, run requests, and automate API workflows through natural language. Useful for exploring, testing, and maintaining APIs directly from an MCP-compatible assistant.
Skills 与 MCP 服务器
有什么区别?Skills定义“做什么”
Skill 将说明、示例提示词和推荐模型组织在一起,让智能体稳定地完成任务。Skills 增加的是知识,而不是新的连接。
MCP 服务器定义“如何连接”
MCP 服务器通过连接数据库、API 和文件等真实系统,为智能体增加新能力。MCP 提供连接和操作,而不是任务说明。
简单来说:当模型需要把某项任务做好时选择 Skill;当模型需要访问工具或系统时选择 MCP 服务器。两者可以组合使用,Skill 可以依赖 MCP 服务器提供的工具。
开发了 MCP 服务器?
将它提交到由社区维护的开源注册表。