agromcp by bedomax - MCP Server

🌾 AgroMCP

AgroMCP is an open-source reference implementation of the Model Context Protocol (MCP) for agricultural data management. It provides a standardized way to expose farm operational data to AI models and applications.

What is MCP?

Model Context Protocol (MCP) is an open standard that enables AI applications to securely access external data sources and tools. Think of it as a universal adapter that lets AI assistants (like Claude, ChatGPT, or Gemini) connect to your data in a structured, secure way.

Why MCP for Agriculture?

Agricultural operations generate vast amounts of data: labor records, costs, crop information, and worker schedules. MCP allows this data to be:

Accessible: AI models can query real farm data instead of making assumptions
Structured: Data follows a consistent schema that AI can reliably parse
Secure: Access is controlled and data remains on your infrastructure
Interoperable: Works with any MCP-compatible AI application

Architecture

┌─────────────┐         ┌──────────────┐         ┌──────────────┐
│   AI Model  │ ◄─────► │   AgroMCP    │ ◄─────► │  Farm Data   │
│ (Claude/GPT)│   MCP   │    Server    │   API   │  (Database)  │
└─────────────┘         └──────────────┘         └──────────────┘

AgroMCP sits between AI models and your farm data, translating AI queries into database requests and formatting responses in a way AI models can understand.

API Endpoints

This implementation exposes the following REST endpoints:

Endpoint	Description	Use Case
`/api/labors`	Agricultural labor activities	"Show me all irrigation tasks from last month"
`/api/costs`	Operational costs and expenses	"What were my fertilizer costs in Q1?"
`/api/workers`	Farm personnel information	"Which workers are certified for pesticide application?"
`/api/crops`	Crop data and growing cycles	"What's the status of my corn harvest?"
`/api/health`	Server health check	System monitoring and uptime

🚀 Quick Start

Local Development

git clone https://github.com/bedomax/agromcp.git
cd AgroMCP
npm install
npm start

The server will start on http://localhost:3000

Deploy to Vercel

Or manually:

npm install -g vercel
vercel

MCP Configuration

The file defines the MCP schema that AI models use to understand available endpoints and data structures. This allows AI to:

Discover what data is available
Understand the structure of requests and responses
Generate appropriate queries automatically

Example MCP usage with Claude Desktop:

{
  "mcpServers": {
    "agromcp": {
      "url": "https://your-deployment.vercel.app/api"
    }
  }
}

Use Cases

Farm Management AI Assistant

"How much did we spend on labor for tomato harvesting last month?"

Predictive Analytics

"Based on historical labor patterns, how many workers will we need for next week's harvest?"

Compliance Reporting

"Generate a report of all workers who handled pesticides this season."

Cost Optimization

"Compare fertilizer costs across all crops and identify savings opportunities."

Data Structure

Currently uses mock data for demonstration. In production, connect to your actual database:

// Example: Connect to PostgreSQL
const { Pool } = require('pg');
const pool = new Pool({
  connectionString: process.env.DATABASE_URL
});

Contributing

Contributions are welcome! This is a reference implementation meant to be extended for real-world agricultural operations.

License

MIT License - feel free to use this in your projects