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Framework Comparison Matrix
Compare 5 leading AI agent frameworks side-by-side
OpenAI Agents SDK
Learning: 3/5
Production: 4/5
Languages: Python, JavaScript/TypeScript
License: MIT (Open Source)
Best For: General-purpose agents, prototyping
Community: 11,000+ GitHub stars
Key Features
- Multi-Agent: Yes, via handoffs
- Memory: Agent state management, session persistence
- RAG: Yes, via function calling
- Streaming: Yes, streaming support
- MCP Support: Yes (official MCP support in 2025)
- Human-in-Loop: Configurable checkpoints
Deployment
Cloud, Local, On-premise
Key Feature: Lightweight, provider-agnostic, official MCP support
LangChain/LangGraph
Learning: 4/5
Production: 5/5
Languages: Python, JavaScript/TypeScript
License: MIT (Open Source)
Best For: RAG, complex workflows, mature projects
Community: 34,000+ GitHub stars
Key Features
- Multi-Agent: Yes, via subgraphs
- Memory: Shared message history, context management
- RAG: Excellent RAG support
- Streaming: Yes, full streaming
- MCP Support: Yes, MCP Adapters package
- Human-in-Loop: Built-in human-in-loop nodes
Deployment
Cloud (LangSmith), Local
Key Feature: MCP Adapters, mature ecosystem, extensive integrations
CrewAI
Learning: 2/5
Production: 4/5
Languages: Python
License: MIT (Open Source)
Best For: Multi-agent teams, collaborative workflows
Community: 20,000+ GitHub stars
Key Features
- Multi-Agent: Yes, role-based crews
- Memory: Short-term, long-term, entity, contextual
- RAG: Yes, via integrations
- Streaming: Yes, streaming support
- MCP Support: Partial (via tool framework)
- Human-in-Loop: Yes, callback handlers
Deployment
Local, Cloud
Key Feature: 2-3x faster multi-agent orchestration, Flows for production
Claude Agent SDK
Learning: 2/5
Production: 5/5
Languages: Python, TypeScript/JavaScript
License: MIT (Open Source)
Best For: MCP-first development, Computer Use, Anthropic models
Community: 55,000+ stars (Claude Code)
Key Features
- Multi-Agent: Yes, via subagents
- Memory: Session persistence, MCP state
- RAG: Yes, via MCP tools
- Streaming: Yes, streaming support
- MCP Support: Full native MCP support
- Human-in-Loop: Fine-grained permissions
Deployment
Cloud, Local, On-premise
Key Feature: MCP-native, Computer Use, Agent Skills framework
LlamaIndex
Learning: 3/5
Production: 4/5
Languages: Python, TypeScript
License: MIT (Open Source)
Best For: Data-intensive RAG, document processing
Community: 47,100+ GitHub stars
Key Features
- Multi-Agent: Yes, via Workflows 1.0
- Memory: Retrieval-augmented context
- RAG: Excellent, primary focus
- Streaming: Yes, streaming support
- MCP Support: Planned support
- Human-in-Loop: Via Workflows
Deployment
Cloud (LlamaCloud), Local
Key Feature: Workflows 1.0, 300+ integrations, durable workflows
Quick Comparison
| Framework | Languages | Learning | Production | License | Multi-Agent | MCP |
|---|---|---|---|---|---|---|
| OpenAI Agents SDK | Python | 3/5 | 4/5 | MIT | – | – |
| LangChain/LangGraph | Python | 4/5 | 5/5 | MIT | – | – |
| CrewAI | Python | 2/5 | 4/5 | MIT | – | – |
| Claude Agent SDK | Python | 2/5 | 5/5 | MIT | – | – |
| LlamaIndex | Python | 3/5 | 4/5 | MIT | – | – |