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Compare 324+ AI Agent Tools

The Developer’s Guide toAI Agent Infrastructure

Every tool gets a structured spec sheet — supported LLMs, MCP support, language, pricing, and live GitHub signals. Not marketing copy.

324Listings5CategoriesUpdated daily from GitHub

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Side-by-side spec sheets across categories

LangGraph
Language

Python, TS

LLMs

Any (via LangChain)

MCP Support

Yes

Multi-Agent

Yes

License

open-source

Stars

32.7K

CrewAI
Language

Python

LLMs

Any (via LiteLLM)

MCP Support

No

Multi-Agent

Yes

License

open-source

Stars

51.9K

AutoGen / AG2
Language

Python

LLMs

OpenAI, Azure, Local

MCP Support

No

Multi-Agent

Yes

License

open-source

Stars

58.3K

OpenAI Agents SDK
Language

Python

LLMs

OpenAI

MCP Support

Yes

Multi-Agent

Yes

License

open-source

Stars

26.6K

Google ADK
Language

Python, Java

LLMs

Gemini, Any

MCP Support

Yes

Multi-Agent

Yes

License

open-source

Stars

19.8K

Anthropic Agent SDK
Language

Python

LLMs

Claude

MCP Support

Yes

Multi-Agent

Yes

License

open-source

Stars

3.5K

Mastra
Language

TypeScript

LLMs

Any (multi-provider)

MCP Support

Yes

Multi-Agent

Yes

License

open-source

Stars

24.2K

CAMEL-AI
Language

Python

LLMs

Any (multi-provider)

MCP Support

No

Multi-Agent

Yes

License

open-source

Stars

17.0K

Also explore

Structured Spec Sheets

Every listing has LLM support, MCP compatibility, pricing, and deployment model

Live GitHub Signals

Stars, commit velocity, downloads — updated daily, not manually

OSS-First Curation

No pay-to-play rankings. Open source tools get equal treatment

Frequently Asked Questions

What is an AI agent framework?
An AI agent framework is a library or SDK that provides the building blocks for creating autonomous AI systems. These frameworks handle agent orchestration, tool calling, memory management, and multi-step reasoning — letting developers focus on defining agent behavior rather than infrastructure. Popular examples include CrewAI for multi-agent teams and PydanticAI for type-safe single agents.
How does DeepYard compare tools?
Every listing on DeepYard has a structured spec sheet with supported LLMs, MCP compatibility, programming language, license type, pricing tier, and deployment model. We pull live GitHub signals (stars, commit velocity, downloads, contributors) daily. No pay-to-play — rankings are driven by real data.
How do I submit a tool to DeepYard?
Visit the Submit page to suggest an AI agent framework, SDK, orchestrator, or developer tool. All submissions are reviewed before being listed. We verify the tool exists, is accessible, and fits one of our categories.

Open Source First

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DeepYard curates the AI agent ecosystem with live GitHub signals, transparent rankings, and a focus on open-source tools. No pay-to-play listings.