Crop Doctor
An AI-powered diagnostic agent that identifies plant health issues and recommends organic treatments using soil and weather metrics.
Project Overview
A secure, multi-agent AI system built using the ADK 2.0 framework that automates plant health diagnostics and organic treatment recommendations. It coordinates three specialized collaborative agents (Orchestrator, Diagnostician, and Treatment Specialist), utilizes a custom Model Context Protocol (MCP) server for local environment and soil simulation, protects user privacy with a robust security checkpoint, and incorporates Human-in-the-Loop review for expert validation before finalizing advice.
The Problem
Smallholder farmers and home gardeners often struggle to diagnose crop diseases accurately. Misdiagnosis leads to incorrect treatments, crop loss, or the unnecessary application of harmful chemical pesticides.
The Solution
Implemented a multi-agent ADK 2.0 workflow that filters inputs through a security checkpoint, leverages a custom MCP server to query simulated soil metrics and local weather, pauses for expert validation (HITL), and presents recommendations in a premium interactive diagnostics dashboard.
The Impact
Bridges the gap between agricultural science and local growers, enabling extension workers to make secure, expert-validated diagnoses in the field while promoting organic agricultural practices.
Date / Year
2026