A2A FEP Consensus Node (MCP Server)

An Agent-to-AI (A2A) negotiation and deadlock-resolution Model Context Protocol (MCP) server built on Free Energy Principle (FEP) spatial dynamics and x402 payment protocols.

Overview

When multiple autonomous LLM agents interact, they often encounter deadlock, semantic stalemate, or hallucination loops. This MCP server exposes deterministic FEP matrix-pruning tools to reduce computational overhead (64x64x1 spatial reduction) and resolve conflicts between competing AI agents using Samurai-Clamp (候) syntax verification.

Related MCP server: TuringWell MCP Server

MCP Capabilities

Tools

• resolve_fep_consensus

  • Description: Resolves semantic deadlocks and conflict states between two or more LLM agents by applying FEP matrix pruning and harmonic phase locking.

  • Input Parameters:

    • agent_proposals (array of strings, required): List of competing agent proposals or reasoning outputs.

    • fep_threshold (number, optional): Free energy reduction sensitivity threshold (default: 0.85).

  • Output: Pruned consensus state, syntax-locked validation token (候), and free energy reduction metrics.

Prompts

• a2a_negotiation_template

  • A structured prompt template to orchestrate multi-agent negotiations utilizing the resolve_fep_consensus tool.

Integration & Protocol Support

• Model Context Protocol (MCP): Fully compliant with MCP v1.0 specification built on Worker edge runtime (GET /.well-known/mcp.json).

• x402 Micro-payments: Native support for 402 Payment Required headers enabling autonomous Agent-to-Agent (A2A) transactions (0.01 USDC on Base / Cloudflare Workers).

Usage & Endpoint

• Hosted MCP Endpoint: https://a2a-fep-consensus.my-agent-api.workers.dev/.well-known/mcp.json

• Method: POST /v1/consensus

https://a2a-fep-consensus.my-agent-api.workers.dev