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+# Model Context Protocol (MCP) Python Implementation
+
+This repository contains a Python implementation of the Model Context Protocol (MCP), demonstrating how to create both a server and client application that communicate using the MCP standard.
+
+## Overview
+
+The MCP implementation consists of two main components:
+
+1. **MCP Server (`server.py`)** - A server that exposes:
+   - **Tools**: Functions that can be called remotely
+   - **Resources**: Data that can be retrieved
+   - **Prompts**: Templates for generating prompts for language models
+
+2. **MCP Client (`client.py`)** - A client application that connects to the server and uses its features
+
+## Features
+
+This implementation demonstrates several key MCP features:
+
+### Tools
+- `completion` - Generates text completions from AI models (simulated)
+- `add` - Simple calculator that adds two numbers
+
+### Resources
+- `models://` - Returns information about available AI models
+- `greeting://{name}` - Returns a personalized greeting for a given name
+
+### Prompts
+- `review_code` - Generates a prompt for reviewing code
+
+## Installation
+
+To use this MCP implementation, install the required packages:
+
+```powershell
+pip install mcp-server mcp-client
+```
+
+## Running the Server and Client
+
+### Starting the Server
+
+Run the server in one terminal window:
+
+```powershell
+python server.py
+```
+
+The server can also be run in development mode using the MCP CLI:
+
+```powershell
+mcp dev server.py
+```
+
+Or installed in Claude Desktop (if available):
+
+```powershell
+mcp install server.py
+```
+
+### Running the Client
+
+Run the client in another terminal window:
+
+```powershell
+python client.py
+```
+
+This will connect to the server and demonstrate all available features.
+
+### Client Usage
+
+The client (`client.py`) demonstrates all the MCP capabilities:
+
+```powershell
+python client.py
+```
+
+This will connect to the server and exercise all features including tools, resources, and prompts. The output will show:
+
+1. Calculator tool result (5 + 7 = 12)
+2. Completion tool response to "What is the meaning of life?"
+3. List of available AI models
+4. Personalized greeting for "MCP Explorer"
+5. Code review prompt template
+
+## Implementation Details
+
+The server is implemented using the `FastMCP` API, which provides high-level abstractions for defining MCP services. Here's a simplified example of how tools are defined:
+
+```python
+@mcp.tool()
+def add(a: int, b: int) -> int:
+    """Add two numbers together
+    
+    Args:
+        a: First number
+        b: Second number
+    
+    Returns:
+        The sum of the two numbers
+    """
+    logger.info(f"Adding {a} and {b}")
+    return a + b
+```
+
+The client uses the MCP client library to connect to and call the server:
+
+```python
+async with stdio_client(server_params) as (reader, writer):
+    async with ClientSession(reader, writer) as session:
+        await session.initialize()
+        result = await session.call_tool("add", arguments={"a": 5, "b": 7})
+```
+
+## Learn More
+
+For more information about MCP, visit: https://modelcontextprotocol.io/