Mpac Multi Principal Agent Coordination

---
name: mpac-multi-principal-agent-coordination
description: 'Research paper: MPAC - A Multi-Principal Agent Coordination Protocol for Interoperable Multi-Agent Collaboration. Extends MCP and A2A protocols for cross-organizational agent collaboration.'
metadata:
  openclaw:
    emoji: "🔗"
    tags: ["research", "arxiv", "multi-agent", "protocol", "coordination", "mcp", "a2a"]
---

# MPAC: A Multi-Principal Agent Coordination Protocol for Interoperable Multi-Agent Collaboration

**arXiv ID:** 2604.15864  
**Published:** 2026-04-17  
**Authors:** Kaiyang Qian, Xinmin Fang, Zhengxiong Li  
**Categories:** cs.MA, cs.AI  
**Utility Score:** 0.95

## Abstract

The AI agent ecosystem has converged on two protocols: the Model Context Protocol (MCP) for tool invocation and Agent-to-Agent (A2A) for single-principal task delegation. Both assume a single controlling principal, meaning one person or organization owns all agents in a workflow. This assumption breaks down in real-world scenarios where agents from different organizations must collaborate.

## Key Contributions

1. **Multi-Principal Coordination**: Enables agents from different organizations to collaborate
2. **Protocol Extension**: Extends beyond MCP and A2A limitations
3. **Interoperability**: Facilitates cross-organizational agent workflows

## Relevance to AI Agent Systems

- **Multi-Agent Coordination**: Core focus on coordinating agents across organizational boundaries
- **Tool Use**: Integrates with MCP for tool invocation
- **Planning**: Supports complex multi-agent planning scenarios
- **Benchmark**: Includes evaluation framework

## Technical Keywords

multi-agent, ai agent, tool, planning, benchmark, coordination

## URL

http://arxiv.org/abs/2604.15864

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**Tracked:** 2026-04-20  
**Source:** arXiv Paper Tracker