ETMCP
  • Getting Started
    • What is MCP?
    • Introduction to ETMCP
  • Agent System
    • Agent Design
    • Missions
  • Incentive Mechanism
  • Technology
    • MCP Technology
    • System Architecture
  • Service List
  • LLM Pricing
  • Future
    • Roadmap
    • Tokenomics and Utility
    • Community
    • FAQ
  • Bonus Programs
    • Referral System
  • API
    • Getting Started (Developer Guide)
  • LEGAL
    • Legal & Licensing
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  1. Agent System

Agent Design

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Last updated 1 day ago

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:

  1. Interpret context via LLM or logic rules

  2. Select and execute tools or sub-agents

  3. Send results for attestation

  4. Return output to users or downstream agents