PrivAI
  • About PrivAI
    • PrivAI’s Solution
  • Mission & Vision
  • Privacy & Automation Core
    • Dynamic Privacy Switching
    • Secure TEE Computation
    • Model Context Protocol (MCP) Bridge
      • Key Functions of the MCP Bridge
  • Ecosystem Features
    • AI Agent Marketplace
      • Create-to-Earn: Developer-Centric Model
      • Rent-to-Use: Permissionless Leasing for Users
      • Agent Discovery and Lifecycle
    • Cross-Chain Interoperability
      • Unified Execution Across Chains
      • Use Case Examples
    • Auditable Privacy Logs
  • Advantages
  • Technology
    • Trusted Execution Environments (TEE)
    • Model Context Protocol (MCP)
    • Agent Virtualization & Modular Deployment
  • Tokenomics
    • Token Allocation
    • Utility
  • Roadmap
  • FAQ
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  1. Technology

Model Context Protocol (MCP)

MCP functions as the task coordination and execution context layer across PrivAI. It defines how agents interact with on-chain contracts, off-chain data, other agents, and the TEE runtime itself. From a technical standpoint, MCP provides:

  • Task context encapsulation: Each agent invocation is packaged with its full operational context — including permission layers, execution history, privacy flags, and input/output schemas

  • Cross-chain execution continuity: MCP enables agents to manage persistent state and decision logic across chains, allowing for workflows like cross-chain arbitrage or multi-step governance proposals

  • Unified communication standard: Whether accessing decentralized storage, invoking smart contracts, or triggering external APIs, all actions are mediated through MCP’s permissioned interface

MCP acts as the logical middleware between the agent execution environment and the broader Web3 ecosystem. It abstracts complex coordination into a programmable protocol layer, allowing agents to behave as context-aware, multi-chain actors with embedded logic for privacy, delegation, and response handling.

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Last updated 4 days ago