Table of Contents

Agent Framework Comparison

A practical side-by-side comparison of all major AI agent frameworks as of Q1 2026. Use this to pick the right framework for your project.

Framework Comparison Table

Framework Language Stars Multi-Agent Memory Tool Use MCP Support Best For
LangChain Python, JS 106k Yes (via LangGraph) Yes Yes (extensive) Yes (community) General-purpose chains, largest ecosystem
LangGraph Python, JS 25k Yes (graph-based) Yes (stateful) Yes Yes (community) Complex stateful workflows, conditional branching
CrewAI Python 45k Yes (role-based crews) Yes Yes Yes Role-based multi-agent teams, rapid prototyping
AutoGen (AG2) Python, .NET 43k Yes (group chat) Yes Yes Yes Conversational multi-agent, enterprise, human-in-loop
DSPy Python 22k No Yes (traces) Limited No Prompt optimization, structured LLM programming
LlamaIndex Python, TS 41k Limited (workflows) Yes (indexing) Yes Yes (community) RAG-first agents, data indexing, knowledge retrieval
OpenAI Agents SDK Python 19k Yes Yes Yes Yes (native) OpenAI-native multi-agent with guardrails
Claude Agent SDK Python, TS N/A Yes Yes Yes Yes (native) Anthropic-native agents, Claude Code foundation
Google ADK Python, Java, TS, Go 18k Yes (hierarchical, A2A) Yes Yes (multimodal) No GCP-native, multimodal, deterministic pipelines
PydanticAI Python 8.4k No Yes (structured) Yes No Type-safe agents, structured outputs, validation
Haystack Python 20k No Yes (pipeline) Yes No Production RAG pipelines, tech-agnostic, evaluation
Agno Python 29k Yes Yes (sessions) Yes Yes Full-stack multi-agent, high performance, observability
Smolagents Python 15k Yes Yes Yes (code agents) No Lightweight HuggingFace agents, code execution
OpenHands Python 46k Yes Yes Yes Yes Autonomous software development, SWE-bench leader
Semantic Kernel C#, Python, Java 24k Yes Yes Yes Yes Microsoft/.NET enterprise, Azure integration

Decision Tree: Picking Your Framework

graph TD A["What kind of agent
are you building?"] --> B["Single agent
with tools"] A --> C["Multi-agent
collaboration"] A --> D["RAG / Data
retrieval agent"] A --> E["Coding / Software
development agent"] B --> B1{"Need type safety
& validation?"} B1 -->|Yes| B2["PydanticAI"] B1 -->|No| B3{"Which LLM
provider?"} B3 -->|OpenAI| B4["OpenAI Agents SDK"] B3 -->|Anthropic| B5["Claude Agent SDK"] B3 -->|Any| B6["LangChain"] C --> C1{"Architecture
preference?"} C1 -->|"Role-based teams"| C2["CrewAI"] C1 -->|"Graph workflows"| C3["LangGraph"] C1 -->|"Chat-based"| C4["AutoGen"] C1 -->|"Enterprise .NET"| C5["Semantic Kernel"] C1 -->|"Full-stack"| C6["Agno"] D --> D1{"Primary need?"} D1 -->|"Data indexing"| D2["LlamaIndex"] D1 -->|"Pipeline flexibility"| D3["Haystack"] D1 -->|"Prompt optimization"| D4["DSPy"] E --> E1["OpenHands"] style A fill:#4a90d9,color:#fff style B2 fill:#2ecc71,color:#fff style B4 fill:#2ecc71,color:#fff style B5 fill:#2ecc71,color:#fff style B6 fill:#2ecc71,color:#fff style C2 fill:#e67e22,color:#fff style C3 fill:#e67e22,color:#fff style C4 fill:#e67e22,color:#fff style C5 fill:#e67e22,color:#fff style C6 fill:#e67e22,color:#fff style D2 fill:#9b59b6,color:#fff style D3 fill:#9b59b6,color:#fff style D4 fill:#9b59b6,color:#fff style E1 fill:#e74c3c,color:#fff

Key Decision Criteria

Criteria Top Pick Runner-Up Notes
Fastest prototyping CrewAI (~35 lines of code) LangChain CrewAI's role abstraction is unmatched for speed
Production graph workflows LangGraph Semantic Kernel LangGraph offers checkpointing + LangSmith observability
Enterprise / Microsoft stack Semantic Kernel AutoGen Native Azure AD, C#/Java/Python support
RAG-first architecture LlamaIndex Haystack LlamaIndex has the deepest indexing pipeline
OpenAI ecosystem OpenAI Agents SDK LangChain Native MCP, built-in guardrails
Anthropic ecosystem Claude Agent SDK Agno Powers Claude Code itself
Google Cloud / multimodal Google ADK LangChain A2A protocol, multi-language support
Autonomous coding OpenHands Smolagents 53%+ SWE-bench, fully autonomous
Lightweight / minimal Smolagents PydanticAI HuggingFace ecosystem, code-execution agents

MCP (Model Context Protocol) Support

MCP is becoming the standard for tool integration. Frameworks with native MCP support allow agents to connect to any MCP server for tools, data sources, and prompts.

Native MCP: OpenAI Agents SDK, Claude Agent SDK, Semantic Kernel, Agno, OpenHands

Community/Plugin MCP: LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex

No MCP yet: DSPy, PydanticAI, Haystack, Google ADK

Last updated: March 2026