MCP Testing Server
This repository contains a testing implementation of a Model Context Protocol (MCP) server.
What is MCP?
The Model Context Protocol (MCP) is an open standard developed by Anthropic to facilitate seamless integration between Large Language Models (LLMs) and external data sources or tools. MCP stands for Model Context Protocol.
MCP provides a standardized way for LLMs to interact with tools, data sources, and other capabilities in a consistent manner, solving the "MxN" integration problem that arises when trying to connect multiple LLMs with various tools.
MCP Architecture
The MCP ecosystem consists of three main components:
- Client: The interface that allows users to interact with LLMs and MCP-enabled tools
- Server: Provides specific functionalities, data access, or tools that LLMs can utilize
- Host: The LLM service (like Claude) that processes inputs and generates outputs
Key Components in MCP
- Client-Server Architecture: MCP uses a client-server model where LLM applications (hosts) connect to servers that provide context and capabilities.
- JSON-RPC Messages: Communication between clients and servers is based on JSON-RPC 2.0 messages, enabling stateful connections and capability negotiation.
MCP Primitives
Server Primitives:
- Prompts: Templated messages or workflows
- Resources: Structured data for LLMs
- Tools: Executable functions for LLMs to perform actions
Client Primitives:
- Roots: Entry points for accessing client-side files
- Sampling: Allows servers to request completions from LLMs, enabling agentic behaviors
Purpose of This Repository
This repository serves as a testing environment for implementing and experimenting with an MCP server. It allows developers to:
- Understand the MCP architecture
- Test MCP server functionalities
- Experiment with different tools and capabilities
- Develop custom MCP integrations
Getting Started
(Detailed installation and setup instructions will be added as the project develops)
Resources
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.