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Model Context Protocol

MCP Official Website

The Model Context Protocol (MCP) website is the central site for understanding the open protocol. The site provides complete documentation, multi-language SDKs, sample servers, and development tools to help developers standardize the connection between large-scale language models and external data sources, APIs, and tools to build more practical AI applications.

2026年4月15日 429 0 浏览 429,收藏 0

mcp.so

mcp.so is a community-driven directory of MCP servers that helps users find and integrate external tools for AI clients like Claude, Cursor, and more. The platform brings together various servers for connecting to databases, development tools, productivity applications, etc., and supports searching, filtering, and community submissions, simplifying the process of extending the functionality of AI assistants.

2026年4月15日 446 0 浏览 446,收藏 0

PulseMCP

PulseMCP is a comprehensive platform focused on the Model Context Protocol (MCP) ecosystem, providing a searchable directory of over 4200 MCP servers, REST APIs, client support and community resources. The platform helps developers seamlessly connect AI models with external tools for automation, content management, financial trading and other scenarios, and includes development documentation, use case demonstrations and information on community activities.

2026年4月15日 343 0 浏览 343,收藏 0

Composio MCP

The Composio MCP platform is based on Model Context Protocol and provides a pre-built server of over 250 tools and more than 20,000 API actions, supporting mainstream services such as Gmail, Slack, GitHub, and more. It has built-in authentication such as OAuth and is compatible with development environments such as Cursor, Claude, GPT, etc., helping developers to quickly build AI applications without having to deal with complex API integration details.

2026年4月15日 405 0 浏览 405,收藏 0

MCP Hub

MCP Hub is a Model Context Protocol-based resource center that provides servers, tools, and documentation to help developers securely connect AI models (e.g., large-scale language models) to enterprise data sources such as databases, Google Drive, Slack, and GitHub.It simplifies the integration of AI with external systems, supports multiple languages , for enterprise data integration and developers building customized AI applications.

2026年4月15日 326 0 浏览 326,收藏 0
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