A tutorial MCP server for learning the Model Context Protocol by building file and system tools. Provides hands-on experience creating custom tools that enable AI models to interact with files and execute system commands.
A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.
A template repository for building Model Context Protocol (MCP) servers that enable LLM clients to interact with custom tools and services through standardized JSON-RPC communication.
An educational repository designed to practice and understand the Model Context Protocol through simple server implementations. It demonstrates core MCP concepts such as tools, resources, and communication via stdio and SSE transport methods.