A complete, production-ready Model Context Protocol (MCP) server designed to help farmers worldwide. This tool provides crop disease detection (AI-ready), treatment recommendations, and a global agricultural knowledge base.
Overview
The Fatin Agro Tool is a production-ready MCP server that enables AI-powered crop disease detection and treatment recommendations for farmers worldwide. Using TensorFlow.js, it analyzes leaf images to identify diseases across supported crops, backed by a knowledge base of common agricultural issues. This server delivers actionable insights directly in applications, helping prevent crop losses without needing on-site experts.
Key Capabilities
- list_supported_crops: Returns a list of supported crops along with their most common diseases, allowing quick reference to coverage.
- detect_crop_disease: Accepts a base64-encoded leaf image, processes it with TensorFlow.js, and outputs the detected crop type and disease with confidence scores.
- recommend_treatment: Takes detected disease details and suggests organic, low-cost treatments based on practical farming practices.
Use Cases
Farmers upload a photo of a suspicious leaf via a mobile app integrated with this MCP server; detect_crop_disease identifies powdery mildew on tomatoes, and recommend_treatment advises a baking soda spray. Agronomists query list_supported_crops to check coverage for regional staples like rice or maize before field surveys. Developers embed the server in farm management software to automate weekly disease scans from drone imagery, triggering alerts with tailored remedies.
Who This Is For
Developers building agritech apps, farmers with basic image-upload interfaces, and extension services needing reliable AI diagnostics. Requires minimal setup for MCP integration and no deep ML expertise, as tools handle TensorFlow.js processing internally. Ideal for those targeting smallholder farms in developing regions.