docs-MCP-server
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This repository contains an implementation of a Model Context Protocol (MCP) server for up-to-date documentation, demonstrating how to build a functional MCP server that can integrate with various LLM clients.
The Model Context Protocol (MCP) server is designed to standardize the way applications provide context to Language Model Models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing AI models to interface with diverse data sources and tools. The MCP server follows a client-server architecture, enabling host applications like IDEs or AI tools to access data through MCP. It supports multiple connections with MCP clients and exposes specific capabilities through the protocol. The server can access both local and remote data sources, providing resources, tools, and prompts to clients. The system requires Python 3.10 or higher, MCP SDK 1.2.0 or higher, and the 'uv' package manager for setup and operation.
Features
- Standardized Protocol: Provides a universal way to connect AI models to various data sources.
- Client-Server Architecture: Supports multiple connections with MCP clients and hosts.
- Resource Access: Allows access to both local and remote data sources.
- Tool Integration: Offers functions that can be called by LLMs with user approval.
- Prompt Templates: Provides pre-written templates to assist users in accomplishing tasks.
