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AI Agent Framework Comparison

Compare AI agent frameworks such as LangChain, CrewAI, AutoGen and Mastra by language, GitHub stars, multi-agent, tool, RAG and MCP support.

AI Agent Framework Comparison

Language:
Multi-agent:
MCP:
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AutoGPT

PythonBeta
v0.6.54 · MIT
187.6k

The viral autonomous agent project. Evolved from a script into a full platform with a visual builder and marketplace.

Multi-agent
Limited
Tools
Yes
Stream
No
RAG
Yes
MCP
No
Medium difficulty

LangChain / LangGraph

PythonProduction
v1.2 / v1.1 · MIT
147.4k

The most popular LLM framework. LangGraph adds stateful, graph-based orchestration for complex multi-step agents.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Via Adapter
High difficulty

AutoGen (Microsoft)

PythonStable
v0.4.4 · MIT
61.2k

Microsoft's multi-agent conversation framework. v0.4 is a complete redesign. Merging with Semantic Kernel into unified Microsoft Agent Framework.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Planned
Medium difficulty

CrewAI

PythonProduction
v1.14.1 · MIT
59.3k

Lean, lightning-fast Python framework for orchestrating role-playing autonomous AI agents. Built entirely from scratch, independent of LangChain.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Yes
Low difficulty

LlamaIndex

PythonProduction
v0.14.20 · MIT
52.4k

The leading framework for building LLM-powered agents over your data. Specializes in connecting, indexing, and querying data from 160+ sources.

Multi-agent
Limited
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Via Adapter
Medium difficulty

Agno (formerly Phidata)

PythonProduction
v2.5.16 · Apache-2.0
42.5k

Build, run, and manage agentic software at scale. Formerly Phidata, rebranded as Agno with 39K+ stars and full MCP support.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Yes
Low difficulty

DSPy (Stanford)

PythonStable
v3.1.3 · MIT
38.5k

The framework for programming -- not prompting -- language models. Uses compilers to optimize prompts and weights automatically.

Multi-agent
No
Tools
Yes
Stream
No
RAG
Yes
MCP
No
High difficulty

OpenAI Agents SDK

PythonBeta
v0.13.6 · MIT
29.8k

Official OpenAI agent framework. Lightweight and powerful with multi-agent handoffs, guardrails, and tracing out of the box.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
No
MCP
Yes
Low difficulty

Smolagents (HuggingFace)

PythonStable
v1.24.0 · Apache-2.0
29.7k

A barebones library for agents that think in code. Minimal abstractions, maximum transparency.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
No
Low difficulty

Semantic Kernel (Microsoft)

.NETProduction
v1.30 · MIT
28.6k

Microsoft's enterprise AI SDK for .NET/Python/Java. Merging with AutoGen into a unified Microsoft Agent Framework.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Yes
Medium difficulty

Mastra

TypeScriptStable
v1.24.0 · Elastic-2.0
28.5k

TypeScript-first AI agent framework from the Gatsby team. Provides workflows, RAG, and first-class MCP support out of the box.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Yes
Medium difficulty

Vercel AI SDK

TypeScriptProduction
v6.0.159 · Apache-2.0
27.1k

The AI toolkit for TypeScript from the creators of Next.js. Over 20 million monthly downloads. Unified API for any LLM provider.

Multi-agent
Limited
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Yes
Low difficulty

Haystack (deepset)

PythonProduction
v2.9 · Apache-2.0
26.6k

AI orchestration framework for building customizable, production-ready LLM applications. Strong focus on RAG and NLP pipelines.

Multi-agent
Limited
Tools
Yes
Stream
Yes
RAG
Yes
MCP
No
Medium difficulty

BabyAGI

PythonAlpha
v2.0 · MIT
22.4k

An experimental framework for a self-building autonomous agent. Minimal by design, used primarily for research and learning.

Multi-agent
No
Tools
Yes
Stream
No
RAG
No
MCP
No
Low difficulty

Google Agent Development Kit

PythonStable
v1.29.0 · Apache-2.0
21.7k

Google's official open-source Python toolkit for building, evaluating, and deploying sophisticated AI agents with native Gemini integration.

Multi-agent
Yes
Tools
Yes
Stream
Yes
RAG
Yes
MCP
Yes
Medium difficulty

Pydantic AI

PythonStable
v1.80.0 · MIT
20.4k

GenAI agent framework the Pydantic way. Type-safe, validated, and production-ready with V1 API stability commitment.

Multi-agent
Limited
Tools
Yes
Stream
Yes
RAG
No
MCP
Yes
Low difficulty

Anthropic Agent SDK

PythonAlpha
v0.1.33 · MIT
8.2k

Official Python SDK for building agents with Claude. Alpha status but rapidly evolving with native MCP support.

Multi-agent
Limited
Tools
Yes
Stream
Yes
RAG
No
MCP
Yes
Low difficulty
Showing 17 of 17 frameworksGitHub stars as of 2026-10-03

Versions, licenses and feature details are curated. Confirm them in each project's repository before adopting.

Updated . Provided as is. Check the output before you rely on it in production.

How to use AI Agent Framework Comparison

  1. 1

    Filter the frameworks

    Filter by language, multi-agent support and MCP support, search by name, or use a quick filter for RAG, multi-agent, MCP, beginner-friendly or enterprise use.

  2. 2

    Compare features

    The table shows multi-agent orchestration, tool calling, streaming, RAG, MCP support, learning curve and maturity for every framework.

  3. 3

    Select two or three to compare

    Tick frameworks in the table or card view and open the side-by-side comparison: version, license, GitHub stars, supported LLM providers and best-fit use cases.

  4. 4

    Confirm before you adopt

    Star counts come from GitHub; versions, licenses and features are curated. Check the project's repository before you commit.

Questions and answers

What is AI Agent Framework Comparison?
An AI agent framework is a library for building LLM applications that plan, call tools and coordinate agents. This comparison covers LangChain/LangGraph, CrewAI, AutoGen, Mastra, LlamaIndex, Semantic Kernel and others by language, license, GitHub stars, multi-agent and MCP support, maturity and learning curve.
Which agent frameworks are included?
Major frameworks including LangChain, LangGraph, CrewAI, AutoGen, Mastra and Semantic Kernel. GitHub star counts are refreshed weekly; framework details are curated.
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Machine-readable contract, endpoints and examples. Humans can ignore this section.

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