A distributed framework for LLM agents
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Updated
Aug 13, 2026 - Python
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
Cross-platform Agent IM for direct Agent-to-Agent communication, secure messaging, and multi-agent collaboration.
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).
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).
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.
Open-source runtime primitives for governed multi-agent systems, persistent Agent Rooms, distributed coordination, inference control and human-agent collaboration.
LangGraph coordinates agents in one process. AXME coordinates them across machines - with durable state and automatic recovery.
Self-hosted collaboration hub for long-running AI agents, shared sessions, and multi-agent dispatch.
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