Open Source Agent Orchestration Tools
Discover 47 open source Agent Orchestration repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. Agent Orchestration projects here are most often combined with AI Agents, Python and Developer Tools. Last updated October 4, 2026.
47 repositories · updated October 4, 2026
autogen: Build Multi-Agent AI Applications
AutoGen is a Python framework for building AI agents that work independently or alongside people. It supports multi-agent orchestration, model and tool integrations, and prototyping, but is now in maintenance mode.
UFO: Automate Desktop Tasks Across Devices with AI Agents
UFO combines a Windows desktop agent with a framework for coordinating agents across devices and platforms. Use it for Windows automation or multi-step workflows that need task planning, device assignment, and parallel execution.
stagewise: Build and Orchestrate Coding Agents in an IDE
stagewise is an agentic IDE that combines a browser preview, coding agent, and codebase editing workflows. It suits developers who want to inspect and change web apps without switching tools, using their own model provider or a stagewise account.
deepagents: Build Agents with Planning and Tooling Built In
Deep Agents is a Python agent harness for building LLM agents with planning, delegation, file access, and context management built in. It suits developers who need a more capable starting point than a minimal agent loop, while retaining control over models and tools.
company-research-agent: Build Source-Backed Company Briefings
Company Research Agent turns a company name into a structured research briefing using specialized agents, web search, and language models. It is suited to teams that want an interactive, self-hosted starting point for company diligence and report generation.
learn-claude-code: Learn to Build LLM Agent Harnesses
A hands-on Python tutorial for building the harness around an LLM coding agent, from a basic tool loop to permissions, memory, teams, and workflows. Suited to developers who want to understand agent infrastructure by studying small runnable examples.
claude-code-by-agents: Coordinate Coding Agents in Shared Rooms
A native macOS app for coordinating Claude Code and other coding agents across local and remote machines. Route requests with @mentions and follow work in threaded rooms backed by OpenAgents workspaces.
mcp-agent: Build Agents with Model Context Protocol
A Python framework for building LLM agents around Model Context Protocol servers and composable workflow patterns. It suits developers who need MCP integrations, multi-agent workflows, or durable execution with Temporal.
deer-flow: Orchestrate Long-Running AI Agent Tasks
DeerFlow is a self-hosted harness for AI agents that coordinate subagents, memory, tools, and sandboxes on tasks that can run from minutes to hours. It suits teams building research, coding, and content workflows that need an extensible agent runtime.
ROMA: Build Hierarchical Multi-Agent Systems
ROMA is a Python framework for solving complex tasks through recursive planning and coordinated agents. It suits developers building extensible multi-agent workflows with LLMs, tools, and optional persistence or API services.
openai-agents-js: Build Multi-Agent and Voice Workflows
A TypeScript SDK for building LLM agents that use tools, delegate work, and manage conversations. It also supports sandboxed tasks and low-latency voice agents, making it useful for teams building more than a single prompt-and-response flow.