
CrewAI gives each agent a role, a goal and a backstory, then hands the crew a list of tasks. The metaphor is its greatest strength and its sharpest limitation.
Everything in the Alpaca Mango archives filed under #ai-agents.

CrewAI gives each agent a role, a goal and a backstory, then hands the crew a list of tasks. The metaphor is its greatest strength and its sharpest limitation.

AutoGen came out of Microsoft Research and modelled work as a conversation between agents. It is now in maintenance mode, superseded by Microsoft Agent Framework — here is what it did, and what carries over.

AutoGen is in maintenance mode and Microsoft points new users at Agent Framework. The underlying question still stands — so here is CrewAI against MAF, and the distinction that decides it.

Every agent framework claims to do the same thing, and none of them do. This is a map of what each one is actually for — sorted by the shape of your problem, not by the vendor's pitch.

MCP turns the N-by-M integration problem into N plus M. Write a server once and any client that speaks the protocol can use your tools — which is why it spread so quickly.

A definition narrow enough to be useful: a model that decides its own next action, in a loop, against real tools. If the sequence is fixed, it is a pipeline — and that is usually better.