The best open source frameworks for building AI agents in 2026
Blog post from Firecrawl
In 2026, the landscape of open-source frameworks for AI agents is diverse, with seven prominent options, including LangGraph, OpenAI Agents SDK, AutoGen, CrewAI, Google ADK, Dify, and Mastra, each offering unique features and catering to different use cases. LangGraph stands out for enterprise adoption with its stateful orchestration and multi-agent support, while Dify excels with a low-code interface attractive to non-technical users. The OpenAI Agents SDK is recognized for its lightweight design and extensive LLM compatibility, whereas AutoGen offers a robust framework for multi-agent conversation with an event-driven architecture. CrewAI is appreciated for its simplicity in role-playing agent orchestration, and Google ADK integrates seamlessly with the Google ecosystem, supporting hierarchical compositions. Mastra, designed for JavaScript and TypeScript, presents graph-based workflows tailored for these environments. Best practices from industry leaders emphasize the importance of selecting appropriate agent types, deploying coordinated systems, and maintaining human values in AI decisions. Firecrawl's innovative web data collection platform complements these frameworks by providing reliable access to web information, essential for developing sophisticated AI agents.