FarmerConnect MCP

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A Model Context Protocol (MCP) service that provides agricultural calculations and location-based weather data for AI agents to assist farmers.

Features

• Agricultural Calculations

  • Land area computation
  • Plant density calculations
  • Yield estimations
  • Unit conversions (weight and length)

• Weather Services

  • Current weather data (temperature and precipitation)
  • Location-based weather information

• Crop Information

  • Get encyclopedic information about a crop.

• Geolocation Services

  • Forward geocoding (place name to coordinates)
  • Reverse geocoding (coordinates to place name)
  • Location caching for improved performance

Installation

# Clone the repository
git clone https://github.com/yourusername/FarmerConnect-MCP.git
cd FarmerConnect-MCP

# Create and activate virtual environment
python -m venv env
.\env\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

Configuration

Create a .env file in the root directory with the following variables:

LOCATIONIQ_API_KEY=your_locationiq_api_key

Usage

Start the MCP server:

python main.py

Available Tools

1. calculate_agro_metric

Performs basic agricultural calculations (land area, plant density, and yield estimate) and unit conversions (weight and length).

2. get_weather_now

Fetches the current weather (temperature and precipitation) for a given location.

• lat (float): Latitude of the location.
• lng (float): Longitude of the location.

3. forward_geocode

Converts a place name into geographic coordinates (latitude and longitude).

• place_name (str): The human-readable location name.

4. reverse_geocode

Converts geographic coordinates into a human-readable place name.

• lat (float): Latitude.
• lng (float): Longitude.

5. get_current_datetime

Gets the server's current date and time.

6. get_crop_info

Provides encyclopedic information about a specific crop in a given location.

• crop_name (str): The common name of the crop (e.g., 'maize', 'cassava').
• location (str): The location (e.g., 'Kenya', 'Nigeria') to provide context.

API Dependencies

• Open-Meteo API (weather data)
• LocationIQ API (geocoding services)
• Wikipedia API (for crop information)

Caching

The service implements request caching for location queries:

• Cache duration: 30 days for LocationIQ requests
• Cache storage: SQLite backend
• Cached methods: GET requests only

License

This project is licensed under the MIT License - see the LICENSE file for details.

For more information about Model Context Protocol, visit the official MCP documentation.