AgentMesh

Distributed Multi-Agent Coordination Runtime

AgentMesh is a production-grade runtime for distributed multi-agent systems, providing the infrastructure needed to deploy, coordinate, and manage large-scale agent teams across distributed compute resources. Built on the actor model paradigm, it treats each agent as an isolated actor with message-passing communication, enabling horizontal scaling without shared state.

A distinctive feature is the AST-based conflict detection system that statically analyzes agent action plans before execution to identify potential resource conflicts, contradictory goals, and circular dependencies. This prevents costly runtime failures in multi-agent workflows where agents may inadvertently interfere with each other's objectives.

The runtime implements production reliability patterns: backpressure for flow control when downstream agents are overloaded, circuit breakers for graceful degradation when external services fail, and dead letter queues for unprocessable messages. These patterns make AgentMesh suitable for long-running agent workflows in production environments.

The system spans 7,000 lines of code with 59 tests covering core functionality. Built on Ray for distributed execution and Python asyncio for local concurrency, AgentMesh supports both local development (single-process mode) and distributed deployment (Ray cluster mode) with the same API.

• Actor model with message-passing for horizontally scalable multi-agent coordination
• AST-based static conflict detection for agent action plans
• Production patterns: backpressure, circuit breakers, dead letter queues
• 7,000 LOC with 59 tests covering core functionality
• Ray + asyncio dual-mode: local development and distributed deployment with same API