CAMEL-AI
Open-source framework for multi-agent task automation
CAMEL-AI is an open-source community and Python framework for building multi-agent systems. It’s aimed at developers and researchers exploring agent behavior, data generation, world simulation, and task automation.
Agenticness = how independently a tool can take action, scored across 9 dimensions. Scored independently by David Kooi, Skylark Creations — see full rubric →
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What's happened with CAMEL-AI lately
- Score changeRubric upgrade v3_0 → v3.1: score 2/32 → 5/362 → 5/36(+3)
Rubric upgrade: agenticness v3.0 (8 dims, /32) → v3.1 (9 dims, /36). Adds Dim 9 (Operator Sovereignty), splits Dim 6 into 6a/6b lenses, tightens Dim 4 autonomous-retry distinction. Not a product change — score shift reflects new dimension + recalibrated rubric, not a change in the tool. Fanout suppressed.
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News mentions sourced from our news feed; score changes from periodic re-evaluations.
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About
CAMEL-AI is an open-source framework and community for multi-agent systems. Based on the website, it is designed for developers and researchers who want to build agent-based workflows for task automation, data generation, and world simulation.
CAMEL-AI looks strongest as a developer-focused agent framework rather than a finished end-user app. The site emphasizes research, benchmarks, and multi-agent experimentation, so it is a better fit if you want to build or study agents than if you want a polished no-code automation product.
Responds to prompts but takes no autonomous action.
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- Free / open source — full functionality available at no cost.
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