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Model Context Protocol MCP Server

Model Context Protocol MCP Server

Public
suspicious-cow/MCP2

Implements a Python-based Model Context Protocol server providing WebSocket JSON-RPC access to tools, resources, and prompts for AI model integration, supporting capability negotiation, discovery, and invocation.

python
0 tools
May 29, 2025
Updated Jun 4, 2025

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Model Context Protocol (MCP) Python Implementation

This project implements a functioning Model Context Protocol (MCP) server and client in Python, following the Anthropic MCP specification. It demonstrates the key patterns of the MCP protocol through a simple, interactive example.

What is MCP?

The Model Context Protocol (MCP) is an open standard built on JSON-RPC 2.0 for connecting AI models to external data sources and tools. It defines a client-server architecture where an AI application communicates with one or more MCP servers, each exposing capabilities such as:

  • Tools: Executable functions that perform actions
  • Resources: Data sources that provide information
  • Prompts: Predefined templates or workflows

MCP standardizes how these capabilities are discovered and invoked, serving as a "USB-C for AI" that allows models to interact with external systems in a structured way.

Project Structure

  • server/: MCP server implementation
    • server.py: WebSocket server that handles MCP requests and provides sample tools/resources
  • client/: MCP client implementation
    • client.py: Demo client that connects to the server and exercises all MCP capabilities

Features Demonstrated

This implementation showcases the core MCP protocol flow:

  1. Capability Negotiation: Client-server handshake via initialize
  2. Capability Discovery: Listing available tools and resources
  3. Tool Invocation: Calling the add_numbers tool with parameters
  4. Resource Access: Reading text content from a resource

Setup

  1. Create a virtual environment:

    python3 -m venv .venv source .venv/bin/activate
  2. Install dependencies:

    pip install -r requirements.txt

Usage

  1. Start the MCP server (in one terminal):

    python server/server.py
  2. Run the MCP client (in another terminal):

    python client/client.py

The client will connect to the server, perform the MCP handshake, discover capabilities, and demonstrate invoking tools and accessing resources with formatted output.

How It Works

MCP Server

The server:

  • Accepts WebSocket connections
  • Responds to JSON-RPC requests following the MCP specification
  • Provides a sample tool (add_numbers)
  • Provides a sample resource (example.txt)
  • Supports the MCP handshake and capability discovery

MCP Client

The client:

  • Connects to the server via WebSocket
  • Performs the MCP handshake
  • Discovers available tools and resources
  • Demonstrates calling a tool and reading a resource
  • Presents the results in a formatted display

Protocol Details

MCP implements these key methods:

MethodDescription
initializeHandshake to establish capabilities
tools/listList available tools
tools/callCall a tool with arguments
resources/listList available resources
resources/readRead resource content
prompts/listList available prompts

Extending the Project

You can extend this implementation by:

  • Adding more tools with different capabilities
  • Adding dynamic resources that change on each read
  • Implementing prompt templates for guided interactions
  • Creating more interactive client applications

References

  • Anthropic Model Context Protocol Spec
  • JSON-RPC 2.0 Specification
  • WebSockets Protocol
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