Agent Design
AI agents in ETMCP come equipped with automation and full context awareness, crafted by the ETMCP team to think, act, and carry out tasks requested by users within decentralized environments. Built to tackle complex tasks, they ensure precision and transparency in every action taken.
Agent Architecture (Context-Centric)
In the MCP-based system, every agent is powered by a Model Context — a structured data packet that includes:
User prompts and goal descriptions
Execution boundaries (resource limits, privacy scope)
Tooling and model access rights
Expected results and verification logic
Agents operate as stateless or stateful compute tasks that:
Interpret context via LLM or logic rules
Select and execute tools or sub-agents
Send results for attestation
Return output to users or downstream agents
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