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Server Learning

Provides a learning environment for understanding and implementing Model Context Protocol (MCP) servers.

About

Server Learning is a project designed to facilitate the understanding and implementation of Model Context Protocol (MCP) servers. It explores key MCP primitives such as Resources, Prompts, Tools, Sampling, and Roots, as well as different transport methods like STDIO and SSE. The project aims to demonstrate how to build an MCP server capable of interacting with clients, handling errors, and exposing functionalities through tools.

Key Features

  • Explores STDIO and SSE transport methods.
  • Demonstrates error handling within the server-client interaction.
  • Highlights the usage of JSON-RPC 2.0 for message formatting.
  • Illustrates the implementation of core MCP primitives like Resources and Prompts.
  • Provides a foundation for understanding and implementing LLM tools.
  • 0 GitHub stars

Use Cases

  • Experimenting with different MCP transport methods.
  • Building custom tools for LLM interaction.
  • Learning the fundamentals of MCP server development.
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