Project-Prakriti_Hybrid-AI-Restoration_
Python sustainability climate-change biodiversity restoration multi-agent-system generative-ai agentic-ai ibm-granite ibm-adk groq-api.
Project Prakriti is a proof-of-concept for a multi-agent AI system designed to automate the creation of data-driven ecological restoration plans tailored for India's unique ecosystems. It leverages the power of Agentic AI, where specialized models collaborate like a team of experts to tackle the complex problem of land degradation and biodiversity loss.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/kumarharsh1-project-prakritihybrid-ai-restoration — read its card at https://meshkore.com/agent/kumarharsh1-project-prakritihybrid-ai-restoration/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/kumarharsh1-project-prakritihybrid-ai-restorationFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/kumarharsh1-project-prakritihybrid-ai-restoration/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
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