"Learning NestJS Framework Knowledge" matching MCP servers:

Enables querying optimal control values (angle for blowers, control for pumps) to minimize power given a required flow rate, using machine learning models trained on pump/fan operation data.

Generates and verifies zero-knowledge proofs locally for Energy Web Verified Compute, keeping private meter readings and blinding salts on the user's machine while enabling agents to submit verifiable proof packages.

Enables AI agents to discover and execute solar energy domain tools such as solar cell simulation, perovskite parameter/bandgap/aging prediction, RAG knowledge retrieval, and curve/table generation through MCP.