Weather MCP Server

# 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](Readme_MCP.md) 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`: ```bash uv init ``` ### 2. Create Virtual Environment Create a virtual environment for the project: ```bash uv venv ``` ### 3. Activate Virtual Environment Activate the virtual environment: **Windows:** ```bash .venv\Scripts\activate ``` **Linux/Mac:** ```bash source .venv/bin/activate ``` ### 4. Install MCP CLI Add the MCP CLI package to enable fast MCP CLI commands: ```bash uv add "mcp[cli]" ``` ## Running the MCP Server ### Development Mode To run the MCP server in development mode: ```bash 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: ```bash 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:** ```json "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: ```bash uv add mcp-use ``` ### Configuration Create a file named `weather.json` and add the following configuration to connect local LLMs to the MCP server: ```json { "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)