I Built the Same AI Agent in 5 Frameworks: What Actually Changes (and What Doesn’t)
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A hands-on comparison of five AI agent frameworks — CrewAI, LangGraph, LlamaIndex, PydanticAI, and Microsoft Agent Framework — built around the same flight-assistant agent. The comparison covers agent setup, tool calling patterns, RAG integration, MCP wiring, and execution flow. Key findings: all frameworks share the same core mental model (agent + tools + run), RAG is effectively just another tool call, and MCP integration is where frameworks diverge most meaningfully. A practical decision guide helps match framework choice to your specific needs: orchestration structure, simple loops, or typed interfaces.
Table of contents
The baseline: one agent, one fair test harnessConcrete takeaways (if you only read one section)1) Agent setup: what you write before anything runs2) Tool calling: same idea, different ergonomics3) RAG: in this comparison, it’s just another tool4) MCP: the “USB-C for tools” (and where frameworks really diverge)5) Execution flow: how you actually run the agent6) What the side-by-side runs reveal (runtime, tokens, and behavior)How to choose a framework (a lightly opinionated guide)Closing: the point of this comparison114 Impressions