MPOP: Multi-LLM Peer Orchestration Protocol Specification v1.0
Description
MPOP (Multi-LLM Peer Orchestration Protocol) defines a standardized framework for enabling multiple Large Language Models to participate in shared conversations as peers.
Abstract
Unlike traditional single-model interactions, MPOP establishes conventions for context sharing, inter-model addressing, turn arbitration, and human authority preservation. This specification is transport-agnostic and implementation-independent, allowing adoption across web applications, mobile clients, CLI tools, and embedded systems.
Key Innovations
- Context Sharing: All participating models receive the complete conversation history including contributions from other models
- @Mention Addressing Protocol: Standardized syntax for direct inter-model communication
- Dynamic Adapter Profiles (DAP): Traffic control mechanism that adjusts participation probabilities without editorial control
- Four-Layer Architecture: L0 (Adapter) → L1 (Facilitator) → L2 (Governance) → User Layer
- Dual Operating Modes: Collaborative v2.5 ("What am I missing?") and Adversarial v3.1 ("Prove it.")
Relationship to MCP
MPOP complements the Model Context Protocol (MCP) which standardizes tool integration. Where MCP defines how models access external tools and data sources, MPOP defines how models communicate with each other.
Conformance Levels
The specification defines four conformance levels: Basic (Level 1), Standard (Level 2), Full (Level 3), and Extended (Level 4), allowing implementations to claim partial compliance.
Document ID: MPOP-2026-01
Notes
Methods
Protocol specification developed through iterative design and implementation experience with multi-LLM orchestration systems. Informed by production deployment of AI Peer Chat platform.Files
MPOP-Protocol-Specification-v1.0.pdf
Files
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Additional details
Related works
- References
- Other: https://modelcontextprotocol.io (URL)
Subjects
- Artificial Intelligence
- https://id.loc.gov/authorities/subjects/sh85008180
- Computer protocols
- https://id.loc.gov/authorities/subjects/sh2008101552
- Multi-agent systems
- https://id.loc.gov/authorities/subjects/sh97001700