--- title: "autogen vs upgini" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-autogen-vs-upgini-upgini" tools: ["microsoft-autogen", "upgini-upgini"] --- # autogen vs upgini *GraphCanon updated Jul 11, 2026* ## Verdict Pick autogen when license: autogen is CC-BY-4.0, upgini is BSD-3-Clause; pick upgini when license: upgini is BSD-3-Clause, 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. [upgini](https://upgini.com) has 354 stars, 26 forks, and 1 open issues, last pushed Jul 7, 2026. Figures are from public GitHub metadata via [autogen's repository](https://github.com/microsoft/autogen) and [upgini's repository](https://github.com/upgini/upgini). | | [autogen](/tools/microsoft-autogen.md) | [upgini](/tools/upgini-upgini.md) | | --- | --- | --- | | Tagline | A programming framework for agentic AI | Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & comme | | Stars | 59,658 | 354 | | Forks | 8,983 | 26 | | Open issues | 945 | 1 | | 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 | BSD-3-Clause | | Categories | AI Agents, LLM Frameworks | Computer Vision, Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autogen](/tools/microsoft-autogen.md) | [upgini](/tools/upgini-upgini.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 87d | 4d | | Open issues (now) | 945 | 1 | | Security scan | No lockfile | 27 low (27 low) | | Full report | [trust report](/tools/microsoft-autogen/trust.md) | [trust report](/tools/upgini-upgini/trust.md) | ## Shared compatibility - **Python**: [autogen](/tools/microsoft-autogen.md) - Python runtime; [upgini](/tools/upgini-upgini.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, upgini is BSD-3-Clause. - 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 upgini if… - License: upgini is BSD-3-Clause, autogen is CC-BY-4.0. - Tags unique to upgini: automated-feature-engineering, automl, automl-pipeline, data-enrichment. - Also covers Computer Vision, Data & Retrieval. - upgini ships Docker support for self-hosted deployment. ## 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 upgini - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - 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 upgini? autogen: A programming framework for agentic AI. upgini: Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & comme. See the comparison table for live GitHub stats and shared categories. ### When should I choose autogen over upgini? Choose autogen over upgini when License: autogen is CC-BY-4.0, upgini is BSD-3-Clause; 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 upgini over autogen? Choose upgini over autogen when License: upgini is BSD-3-Clause, autogen is CC-BY-4.0; Tags unique to upgini: automated-feature-engineering, automl, automl-pipeline, data-enrichment; Also covers Computer Vision, Data & Retrieval; upgini ships Docker support for self-hosted deployment. ### 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 upgini? Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is autogen or upgini more popular on GitHub? autogen has more GitHub stars (59,658 vs 354). Stars measure visibility, not whether either tool fits your constraints. ### Are autogen and upgini open source? Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, upgini: BSD-3-Clause). ### Where can I find alternatives to autogen or upgini? GraphCanon lists graph-backed alternatives at [autogen alternatives](/tools/microsoft-autogen/alternatives) and [upgini alternatives](/tools/upgini-upgini/alternatives) ([autogen markdown twin](/tools/microsoft-autogen/alternatives.md), [upgini markdown twin](/tools/upgini-upgini/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-upgini-upgini.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autogen or upgini? autogen: Steady. upgini: Very active. 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 upgini? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autogen trust report](/tools/microsoft-autogen/trust); [upgini trust report](/tools/upgini-upgini/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/_