MCP Server Creation and MCP client connection (Agent-Claude,cursor or, custom server calling and integration with local LLMs).

This project demonstrates how to create and connect an MCP (Model Context Protocol) weather server using FastMCP.

📖 Want to learn more about MCP? Check out our Comprehensive MCP Guide for detailed explanations, concepts, and best practices.

Prerequisites

• Python 3.13+
• uv package manager installed

Setup Instructions

1. Initialize the Project

Initialize a new project using uv:

uv init

2. Create Virtual Environment

Create a virtual environment for the project:

uv venv

3. Activate Virtual Environment

Activate the virtual environment:

Windows:

.venv\Scripts\activate

Linux/Mac:

source .venv/bin/activate

4. Install MCP CLI

Add the MCP CLI package to enable fast MCP CLI commands:

uv add "mcp[cli]"

Running the MCP Server

Development Mode

To run the MCP server in development mode:

uv run mcp dev server/weather.py

Expected Output:

Starting MCP inspector...

⚙️ Proxy server listening on localhost:6277

Connecting to Claude Desktop

Install Server to Claude

Add the weather server to Claude Desktop:

uv run mcp install server/weather.py

Expected Output:

Added server 'weather' to Claude config 

Successfully installed weather in Claude app

Once installed, you can ask Claude questions like:

• "What are the weather alerts in CA?"
• The MCP server will be called automatically and display the results.

Manual Configuration for Cursor or Other Clients

For Cursor or other clients, you'll need to manually configure the server using the Claude Desktop config file format.

Get the server configuration from: claude_desktop_config file

Example Configuration:

"weather": {
  "command": "C:\\Users\\gaura\\AppData\\Local\\Programs\\Python\\Python313\\Scripts\\uv.EXE",
  "args": [
    "run",
    "--with",
    "mcp[cli]",
    "mcp",
    "run",
    "C:\\Users\\gaura\\OneDrive\\Desktop\\AI projects\\mcp_project\\server\\weather.py"
  ]
}

Note: Update the paths in the configuration to match your system paths.

Usage in Cursor:

• Go to MCP → mcp config.json
• Add the configuration above

Using MCP with Local LLMs (mcp-use)

mcp-use allows you to connect to MCP servers directly without an AI agent for programmatic tool access. This is useful for custom server calling and integration with local LLMs.

Installation

Install the mcp-use package:

uv add mcp-use

Configuration

Create a file named weather.json and add the following configuration to connect local LLMs to the MCP server:

{
  "mcpServers": {
    "weather": {
      "command": "C:\\Users\\gaura\\AppData\\Local\\Programs\\Python\\Python313\\Scripts\\uv.EXE",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "C:\\Users\\gaura\\OneDrive\\Desktop\\AI projects\\mcp_project\\server\\weather.py"
      ]
    }
  }
}

Note: Update the paths in the configuration to match your system paths.

References

• FastMCP: https://github.com/jlowin/fastmcp

  • Create MCP servers and connect them to different clients like Claude, Cursor, etc.

• mcp-use: https://github.com/mcp-use/mcp-use

  • Connect to MCP servers directly without an AI agent for programmatic tool access (custom server calling and use)