# multi-agent

Open-source agentic development environment for parallel AI agents

Emdash is an open-source agentic development environment for orchestrating many coding agents in parallel. It runs each agent in an isolated Git worktree, presents tasks in a dashboard, auto-detects installed CLIs, works with 25+ agents including Claude Code, Codex, Cursor, Amp and Gemini, and supports MCP server connections for tool access.

Open-source AI agent framework with persistent memory, reusable skills, tools, and messaging gateways

Hermes Agent is an open-source AI agent framework with persistent memory, reusable skills, 40+ tools, cron jobs, and messaging gateways.

Python and TypeScript framework for production multi-agent systems

BeeAI Framework is an Apache-2.0 toolkit for building production-ready AI agents and multi-agent systems in Python and TypeScript. Its docs cover agents, tools, RAG, memory, workflows, backend providers, serving, and A2A/MCP integration surfaces, making it a vendor-neutral option for teams comparing LangGraph, CrewAI, Mastra, and related agent runtimes.

Cross-agent messaging for CLI coding agents

agmsg is an MIT-licensed Bash and SQLite messaging layer for CLI coding agents. It lets Claude Code, Codex, Gemini CLI, GitHub Copilot CLI, Antigravity, OpenCode, Hermes, and other terminal agents exchange messages through a shared local database instead of relying on a human copy-paste relay. It is intentionally not MCP, not a broker, and not a subagent framework.

xAI's terminal coding agent with parallel subagents and worktree-aware automation

Grok Build is xAI's terminal-first coding agent for planning, editing, testing, and reviewing code from a local CLI. The early beta exposes subagent controls, worktree mode, headless JSON output, best-of-N parallel attempts, sandbox profiles, and experimental memory. It fits developers comparing Claude Code, Codex, and Gemini CLI for local agentic workflows with deeper parallel execution.

The Agent Development Environment for running parallel coding agents in isolated worktrees

Orca is an open-source Agent Development Environment (ADE) for running 25+ coding agents in parallel, each in an isolated git worktree. Supports Claude Code, Codex, Gemini, OpenCode, Amp, Goose, Grok, and Aider with BYOK subscriptions. Includes a WebGL terminal with infinite splits, built-in git tracking, hot-swap accounts, and an iOS/Android companion app for monitoring agent work on the move.

AI agent dev environment with parallel git worktrees, magic git commands, and Linear integration.

Jean is an open-source desktop dev environment for AI agents from coolLabs (the team behind Coolify). It runs multiple coding agents — Claude Code, Codex, and others — in parallel inside isolated git worktrees, each with its own chat session and terminal. Magic git commands handle commits, PR descriptions, code reviews, and merge conflicts with AI assistance, while built-in Linear and GitHub integrations load issue context into every session.

Rust-native multi-agent orchestration for production

GraphBit is a Rust-native, multi-agent orchestration framework built for production. It targets the gap between Python-first frameworks like LangGraph and the operational expectations of enterprise systems — predictable memory, low latency, deterministic concurrency, and the ability to embed an agent runtime in services that already run Rust without dragging in a Python interpreter.

Multi-agent AI coding platform with orchestrated specialist agents

Zencoder is an AI coding platform that uses multi-agent orchestration to handle complex development tasks. Specialist agents collaborate on different aspects of implementation including code generation, testing, documentation, and review. Integrates with VS Code and JetBrains IDEs. Features repository-aware context that understands project architecture and coding standards.

Multi-agent orchestration plugin for Claude Code

Oh My ClaudeCode (OMC) is a plugin for Claude Code that adds multi-agent orchestration with 19 specialized agents, smart model routing between Haiku and Opus, and execution modes such as Autopilot, Team, Ralph, Ultrawork, and Deep Interview. It provides lifecycle hooks, a real-time HUD statusline, and source-backed Claude Code workflows that turn one session into a coordinated AI development team.

Open-source personal AI agent for messaging apps

OpenClaw is a free, open-source AI agent framework that turns any LLM into an autonomous personal assistant accessible through messaging apps like WhatsApp, Telegram, Discord, and Signal. Running entirely on your local machine via a Node.js gateway, it connects AI models to system tools, browsers, files, and APIs for multi-step task execution with persistent memory across sessions.

BEAM/Elixir-native framework for durable multi-agent systems

Jido is an Elixir-native AI agent framework that leverages the BEAM virtual machine's concurrency and fault-tolerance for building durable, distributed multi-agent systems. It provides primitives for agent lifecycle management, skill composition, and message-based coordination. Designed for teams running Elixir in production who need agent capabilities. Apache-2.0 with 1,600+ GitHub stars.

Open-source AI coworker with persistent memory and tool use

Rowboat is an open-source AI coworker platform that provides persistent memory, tool use, and multi-agent orchestration in a chat-based interface. It enables teams to build AI assistants that remember context across sessions, access internal tools and databases, and coordinate specialized sub-agents for complex workflows. Over 9,300 GitHub stars.

Multi-agent orchestration with 10+ swarm patterns

Swarms is an enterprise-grade multi-agent orchestration framework with 6,100+ GitHub stars that provides 10+ swarm patterns including sequential, concurrent, hierarchical, mixture-of-agents, and graph-based workflows. The SwarmRouter lets teams switch between orchestration strategies by changing a single parameter. It supports MCP for tool integration, multi-model providers via Anthropic, OpenAI, and local models, and includes an AutoSwarmBuilder that generates agents from task descriptions.

No-code platform for building AI agent workforces

Relevance AI is a no-code platform from Sydney, Australia for building and deploying AI agent workforces that execute business workflows autonomously. Backed by a $24M Series B led by Bessemer Venture Partners, it offers 9,000+ integrations, a visual agent builder, a marketplace of pre-built agents, and multi-model support across OpenAI, Anthropic, and AWS Bedrock. Agents handle sales development, lead research, meeting prep, onboarding, and support workflows.

Multi-agent programming framework inspired by the Actor model

Langroid is a lightweight Python framework from CMU and UW-Madison researchers for building LLM applications using a multi-agent programming paradigm inspired by the Actor Framework. Agents are first-class citizens that encapsulate LLM state, vector stores, and tools, then collaborate via message passing through hierarchical task delegation. With 3,900+ GitHub stars, Langroid works with any LLM provider and does not depend on LangChain or other frameworks.

Build AI agents like LEGO — modular and predictable

Atomic Agents is a lightweight Python framework by BrainBlend AI that applies Atomic Design principles to AI agent development. Each component — agents, tools, context providers — is a single-purpose, reusable building block with Pydantic-enforced input/output schemas for type safety. Built on Instructor for structured LLM outputs, it prioritizes predictability and developer control over the autonomous-but-unpredictable behavior of larger frameworks like LangChain or CrewAI.

Multi-agent coordination framework

A framework for coordinating multiple AI agents working together on complex development tasks. Defines agent roles, communication patterns, task delegation strategies, and inter-agent workflows to break down large projects into manageable, parallel workstreams handled by specialized agents. Ideal for teams experimenting with multi-agent architectures where different AI models handle distinct aspects of software development.

Open-source dashboard for AI agent orchestration

An open-source dashboard for managing AI agent fleets. Dispatch tasks, monitor progress, and orchestrate multiple agents working in parallel on your codebase. Provides real-time visibility into agent activity, error tracking, and resource allocation so teams can scale autonomous coding workflows with confidence.

Multi-agent CLI pair programmer with FORGE, MUSE, and SAGE agents

Model-agnostic terminal coding tool with 3 specialized agents: FORGE for code editing, MUSE for planning and review, and SAGE for research. Connects to hundreds of LLM providers and models with local-first privacy and conversational Git integration. Apache 2.0 licensed. A thoughtfully designed multi-agent approach that separates concerns between coding, thinking, and information gathering for more reliable results.

Run Claude Code, Codex, and Gemini agents in parallel with isolated branches

Open-source desktop app for orchestrating multiple AI coding agents simultaneously. Auto-creates git worktrees per agent and symlinks shared dependencies to prevent conflicts between parallel tasks. Designed for teams and power users who want to run several AI agents on different features or bugs at the same time, maximizing throughput while keeping each agent's changes cleanly isolated.

Run a team of AI coding agents in parallel on your Mac

Web-based dashboard for monitoring and managing multiple AI coding agent sessions. Provides real-time visibility into what each agent is doing, resource consumption, and task progress across your team. Centralizes agent management so team leads can assign work, review outputs, and track productivity across multiple concurrent AI-assisted development workflows from a single interface.

Agent Development Kit by Google

Google's open-source framework for building AI agents with Gemini models. Supports multi-agent orchestration, tool use, and deployment to Vertex AI or Cloud Run. Provides a structured approach to agent development with built-in evaluation, testing, and monitoring capabilities, making it the official path for teams building agent systems within the Google Cloud ecosystem.

Official Python SDK for OpenAI agents

OpenAI's Python framework for building multi-agent AI applications with GPT models. Provides primitives for creating agents with tool calling, handoffs between specialized agents, guardrails for input/output validation, and tracing for observability. Supports building complex workflows where agents collaborate on tasks. Includes built-in tools for file search, code execution, and web browsing. Designed for production agent systems with structured output and error recovery patterns.