MCP-Server-101
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MCP-Server-101 is a robust implementation of the Model Context Protocol (MCP), designed to facilitate seamless integration and interaction with various documentation sources.
MCP-Server-101 is a powerful server implementation of the Model Context Protocol (MCP), aimed at enhancing the interaction between AI models and external data sources. It provides essential tools for querying and extracting relevant information from documentation, making it a valuable resource for developers working with libraries such as langchain, openai, and llama-index. The server uses a client-server architecture where AI applications (hosts) communicate with MCP clients to access functionalities exposed by lightweight MCP servers. These servers interface with local files, databases, APIs, or other services to provide resources, tools, and prompts. MCP-Server-101 supports environment configuration, web search, web content fetching, and documentation search, ensuring efficient and secure data handling.
Features
- Environment Configuration: Uses dotenv to load environment variables for secure and flexible configuration management.
- Web Search: Performs web searches using the Serper.dev API, retrieving up to two results for a given query.
- Web Content Fetching: Fetches and parses visible text content from a webpage using httpx and BeautifulSoup.
- Documentation Search Tool: Allows users to search documentation for specific queries within supported libraries like langchain, openai, and llama-index.
- Server Execution: Executed using the mcp.run method with stdio transport for integration with other tools and systems.
Tools
get_docs
Searches documentation for specific queries within supported libraries.
