MCP Project Setup

This document outlines the steps to set up the mcp project environment.

1. Create Conda Environment

Create a new conda environment named mcp with Python 3.12:

2. Install uv

Install the uv package manager using the following command:

3. Install fastmcp

Install the fastmcp package using uv in the mcp environment:

4. Verify Installation

Confirm the fastmcp installation by running the following command:

5. Running the Hello World Server

mcp_hello.py is a "hello world" type mcp server. You can run the MCP inspector for it using the following command:

6. Connecting with Proxy Session Token

Copy the provided session token from CLI, click on the provided link, paste in Configuration -> Proxy Session Token, click connect.

7. Inspect hello_world tool

Click on Tools in the top menu bar. "hello_world" should be listed with a parameter "name". Input your name and click "Run Tool". The tool should succeed and return a greeting.

8. Running Resource Tests

mcp_resources.py defines MCP resources. You can run tests for these resources using the --test argument:

9. Weather Server

mcp_weather.py exposes a tool to get current weather data from OpenWeatherMap.

Before running: Ensure you have set your OPENWEATHER_API_KEY in the .env file:

To run the weather server manually:

To run tests for the weather tool:

10. Integrating with Gemini CLI

To allow the Gemini CLI to automatically start and connect to your mcp_weather server, you need to configure its settings.json file.

1. Locate The settings.json file is typically located at:

   • Linux/macOS: ~/.gemini/settings.json

   • Windows: %APPDATA%\gemini\settings.json

   If the file or directory does not exist, create them.

2. Add Add the following entry to the mcpServers section in your settings.json file. Replace /mnt/d/Projects/_sandbox/mcp/ with the absolute path to your mcp project directory.

   { "mcpServers": { "weather_server": { "command": "uv", "args": [ "run", "/mnt/d/Projects/_sandbox/mcp/mcp_weather.py" ], "cwd": "/mnt/d/Projects/_sandbox/mcp", "timeout": 10000 } } }

   Once configured, when you run gemini, the CLI will automatically start your mcp_weather.py server and make its get_current_weather tool available to the Gemini model.

References

• Gemini CLI Configuration: https://github.com/google-gemini/gemini-cli/blob/main/docs/cli/configuration.md - For information on setting up MCP with the Gemini CLI.

• FastMCP: https://github.com/jlowin/fastmcp - The FastMCP library used for building MCP servers.