Multi-Agent Systems on GitHub in 2026: 10 Frameworks with Real Stars

Ten multi-agent frameworks on GitHub ranked by real stars, from AutoGen to AgentVerse.

## Multi-Agent Systems on GitHub in 2026 Multi-agent systems let multiple AI agents collaborate on one task. Star data below is from the GitHub API snapshot on 2026-07-31. ### The frameworks 1. **microsoft/autogen** - 60,129 stars. The most-starred multi-agent framework; conversation-based agents with AutoGen Studio. 2. **joaomdmoura/crewAI** - 56,432 stars. Role-based crews that delegate tasks; beginner-friendly. 3. **langchain-ai/langgraph** - 38,573 stars. Graph-based orchestration; the production choice, supports human-in-the-loop. 4. **phidatahq/phidata** - 41,526 stars. Multi-agent teams with built-in UI and monitoring. 5. **OpenBMB/AgentVerse** - 5,091 stars. Research framework for multi-agent simulation. 6. **microsoft/TaskWeaver** - 6,176 stars. Code-first multi-agent workflows. 7. **ai16z/eliza** - 18,856 stars. Agent framework with multi-agent social capabilities. 8. **camel-ai/camel** - 30k+ stars. Role-playing multi-agent framework from academic research. 9. **OpenDevin/OpenHands** - 82,697 stars. Multi-agent software development (planner + executor + verifier). 10. **meta-llama/llama-models** - 7,664 stars. Reference implementations including multi-agent examples. ### Patterns to know - **Orchestrator-worker**: one manager delegates to specialized workers (LangGraph) - **Conversation**: agents talk to each other until consensus (AutoGen) - **Role-playing**: agents simulate personas (CAMEL, AgentVerse) ### How to start Begin with CrewAI: define 2-3 roles, give them tasks, and let the crew run. Move to LangGraph when you need deterministic control. ### FAQ **Is multi-agent better than single-agent?** For tasks with separable subtasks, yes - research and industry both show gains; for simple Q and A, no. **What is the token cost?** Multi-agent multiplies token usage - each agent is a full LLM conversation. Budget 3-10x a single agent.