Compare the best frameworks for building autonomous AI agents — from single-agent SDKs to multi-agent orchestration platforms.
A transparent, minimal, and hackable agent framework. ~300 lines of readable code. Full control, no magic.
[NAACL2025] LiteWebAgent: The Open-Source Suite for VLM-Based Web-Agent Applications
Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI
AgentEval is the comprehensive .NET toolkit for AI agent evaluation—tool usage validation, RAG quality metrics, stochastic evaluation, and model comparison—built first for Microsoft Agent Framework (MAF) and Microsoft.Extensions.AI. What RAGAS, PromptFoo and DeepEval do for Python, AgentEval does for .NET
🤖 The most comprehensive directory of AI agent frameworks, platforms, tools, and resources - hundreds of curated entries covering open-source, no-code, enterprise, and autonomous solutions. NEW Boilerplates!
A curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (RAG, Agents).
An autonomous agent that takes work, does work, gets paid, and gets better at it.
| Tool | Stars | Language | License | Score |
|---|---|---|---|---|
| AgenticFORGE | ★ 61 | TypeScript | — | 35 |
| agentsilex | ★ 439 | Python | MIT | 40 |
| hive | ★ 9.9k | Python | Apache-2.0 | 48 |
| LiteWebAgent | ★ 145 | Python | — | 30 |
| LiteMultiAgent | ★ 102 | Python | — | 24 |
| agentops | ★ 5.4k | Python | MIT | 43 |
| AgentEval | ★ 67 | C# | MIT | 35 |
| Ultimate-Agent-Directory | ★ 50 | Python | MIT | 37 |
| awesome-azure-openai-llm | ★ 396 | Python | — | 38 |
| cashclaw | ★ 338 | TypeScript | MIT | 40 |
The top ai agent frameworks tools include AgenticFORGE, agentsilex, hive. These are ranked by our composite score based on GitHub stars, community activity, and code quality.
Most tools listed here are open-source. 6 out of 10 have explicit open-source licenses, making them free to use and modify.
Consider your tech stack (language compatibility), project scale (stars indicate community trust), and specific features you need. Use the comparison table above to evaluate side by side.
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