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
Enables AI agents to interact with Amazon Web Services through the Model Context Protocol. Provides access to core AWS services including S3, Lambda, DynamoDB, CloudWatch, and IAM. Supports resource discovery, log analysis, and infrastructure management with proper credential handling and region awareness.
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.
Google Cloud's MCP server for deploying and managing applications on Cloud Run, giving coding agents a guided path from source code to a serverless production service.
Firebase's MCP integration exposes Firebase project context and development workflows to coding agents for building, testing, and operating Firebase applications.
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。