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
MCP server for Replicate, which hosts thousands of open machine learning models behind a single API. Lets AI agents search models, run predictions (image, video, audio, and text generation), poll prediction status, and retrieve outputs. Useful for adding generative media and specialized ML capabilities to agent workflows without managing infrastructure.
Cloudinary's official MCP servers for managing media through conversational AI. Cover the full media workflow: uploading and transforming images and videos, organizing assets with structured metadata, configuring processing pipelines, and running AI-powered content analysis. Available as remote OAuth endpoints or local npx processes across several focused servers (asset management, environment config, structured metadata, and analysis).
Official Semgrep MCP server for static application security testing. Lets AI agents scan code for security vulnerabilities and bugs, run custom rules, and return findings with severity and remediation guidance, embedding SAST into AI-powered development workflows.
Community MCP server that connects a personal WhatsApp account to AI assistants. Using the WhatsApp multi-device web API, it lets agents search and read your messages and contacts and send messages, including media. Messages are stored locally in SQLite and only shared with the model when the agent accesses them through tools, keeping data on your machine.
Automattic's MCP server that connects AI assistants such as Claude Desktop to WordPress sites. Supports multiple authentication methods (OAuth 2.0, JWT, and application passwords) and exposes the WordPress REST and WP-CLI capabilities so agents can read and manage posts, pages, media, and site settings through natural language.
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。