distributed-agents

A distributed framework for LLM agents

Durable execution framework for AI agents in Go. Keeps agent state, tool calls, and execution loops resilient across process crashes.

Peer-to-peer communication for AI coding agents. 8 MCP tools, full CLI, Python client. Part of the Qualixar research initiative by Varun Pratap Bhardwaj.

A framework for building multi-agent AI systems. Enables LLMs to collaborate through hierarchical organization, parallel task execution, and extensible tools.

Composable primitives for goal-directed coordination in Go. Synchronization, resource allocation, and collective intelligence that adapt through multiple strategies. Built with capacity for systems with 1000+ independent agents.

Multi-agent systems framework for the BEAM platform - build distributed autonomous agents with OTP supervision and fault tolerance

Distributed Multi-Agent AI Orchestration with Ollama - Advanced collaborative workflow with AST quality voting, TrustCall validation, and adaptive strategy selection

A minimal protocol for task exchange between autonomous AI agents (TASK → RESULT | ERROR).

Experimental Hermes power-user Kanban labs: remote Docker workers, distributed execution, and sharded-model worker backends ahead of upstream stabilization.

두레클로 — 분산 디바이스 AI 에이전트 협력 오케스트레이션 | Distributed AI agent crew orchestration

LangGraph agents that coordinate across machines with durable execution, retries, and human approval.

Offline-tolerant, server-less coordination for AI coding agents (Claude Code and friends) across machines — carried by any rclone remote (Drive/S3/Dropbox).

Open-source runtime primitives for governed multi-agent systems, persistent Agent Rooms, distributed coordination, inference control and human-agent collaboration.

Coordinate distributed Codex workers to solve, review, and submit patches for approved open-source projects.

Distributed execution for agents — gateway/worker architecture for running agent fleets in isolated Docker runtimes. Part of the nano series.

Horizontally scaled coding agents + behaviour analytics (FastAPI, Redis workers, eval harness)

Self-hosted collaboration hub for long-running AI agents, shared sessions, and multi-agent dispatch.

LangGraph coordinates agents in one process. AXME coordinates them across machines - with durable state and automatic recovery.