--- title: "autogen vs metric-learn" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-autogen-vs-scikit-learn-contrib-metric-learn" tools: ["microsoft-autogen", "scikit-learn-contrib-metric-learn"] --- # autogen vs metric-learn *GraphCanon updated Jul 12, 2026* ## Verdict Pick autogen when license: autogen is CC-BY-4.0, metric-learn is MIT; pick metric-learn when license: metric-learn is MIT, autogen is CC-BY-4.0. [autogen](https://microsoft.github.io/autogen/) reports 60k GitHub stars, 9.0k forks, and 945 open issues, last pushed Apr 15, 2026. [metric-learn](http://contrib.scikit-learn.org/metric-learn/) has 1.4k stars, 232 forks, and 51 open issues, last pushed Mar 19, 2026. Figures are from public GitHub metadata via [autogen's repository](https://github.com/microsoft/autogen) and [metric-learn's repository](https://github.com/scikit-learn-contrib/metric-learn). | | [autogen](/tools/microsoft-autogen.md) | [metric-learn](/tools/scikit-learn-contrib-metric-learn.md) | | --- | --- | --- | | Tagline | A programming framework for agentic AI | Metric learning algorithms in Python | | Stars | 59,658 | 1,437 | | Forks | 8,983 | 232 | | Open issues | 945 | 51 | | Language | Python | Python | | Adopt for | AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models. | - | | Persona | - | - | | Runtime | - | - | | License | CC-BY-4.0 | MIT | | Categories | AI Agents, LLM Frameworks | Computer Vision, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autogen](/tools/microsoft-autogen.md) | [metric-learn](/tools/scikit-learn-contrib-metric-learn.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 87d | 114d | | Open issues (now) | 945 | 51 | | Full report | [trust report](/tools/microsoft-autogen/trust.md) | [trust report](/tools/scikit-learn-contrib-metric-learn/trust.md) | ## Shared compatibility - **Python**: [autogen](/tools/microsoft-autogen.md) - Python runtime; [metric-learn](/tools/scikit-learn-contrib-metric-learn.md) - Python runtime ## Decision facts: autogen - **Requirements:** Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure. - **Adopt for:** AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models. ## Choose when ### Choose autogen if… - License: autogen is CC-BY-4.0, metric-learn is MIT. - Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.. - Tags unique to autogen: agentic-agi, agents, ai, autogen. - Also covers AI Agents. - You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### Choose metric-learn if… - License: metric-learn is MIT, autogen is CC-BY-4.0. - Tags unique to metric-learn: machine-learning, metric-learning, python, scikit-learn. - Also covers Computer Vision. ## When NOT to use autogen - If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. - When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. - You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities. ## When NOT to use metric-learn - Last GitHub push was 114 days ago (slowing maintenance, Mar 19, 2026). Validate activity before betting a new project on metric-learn. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between autogen and metric-learn? autogen: A programming framework for agentic AI. metric-learn: Metric learning algorithms in Python. See the comparison table for live GitHub stats and shared categories. ### When should I choose autogen over metric-learn? Choose autogen over metric-learn when License: autogen is CC-BY-4.0, metric-learn is MIT; Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.; Tags unique to autogen: agentic-agi, agents, ai, autogen; Also covers AI Agents; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### When should I choose metric-learn over autogen? Choose metric-learn over autogen when License: metric-learn is MIT, autogen is CC-BY-4.0; Tags unique to metric-learn: machine-learning, metric-learning, python, scikit-learn; Also covers Computer Vision. ### When should I avoid autogen? If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities. ### When should I avoid metric-learn? Last GitHub push was 114 days ago (slowing maintenance, Mar 19, 2026). Validate activity before betting a new project on metric-learn. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is autogen or metric-learn more popular on GitHub? autogen has more GitHub stars (59,658 vs 1,437). Stars measure visibility, not whether either tool fits your constraints. ### Are autogen and metric-learn open source? Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, metric-learn: MIT). ### Where can I find alternatives to autogen or metric-learn? GraphCanon lists graph-backed alternatives at [autogen alternatives](/tools/microsoft-autogen/alternatives) and [metric-learn alternatives](/tools/scikit-learn-contrib-metric-learn/alternatives) ([autogen markdown twin](/tools/microsoft-autogen/alternatives.md), [metric-learn markdown twin](/tools/scikit-learn-contrib-metric-learn/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/microsoft-autogen-vs-scikit-learn-contrib-metric-learn.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autogen or metric-learn? autogen: Steady. metric-learn: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for autogen and metric-learn? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autogen trust report](/tools/microsoft-autogen/trust); [metric-learn trust report](/tools/scikit-learn-contrib-metric-learn/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=microsoft-autogen`](/api/graphcanon/graph?tool=microsoft-autogen) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_