--- title: "autogen vs plexiglass" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-autogen-vs-safellama-plexiglass" tools: ["microsoft-autogen", "safellama-plexiglass"] --- # autogen vs plexiglass *GraphCanon updated Jul 11, 2026* ## Verdict Pick autogen when license: autogen is CC-BY-4.0, plexiglass is Apache-2.0; pick plexiglass when license: plexiglass is Apache-2.0, 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. [plexiglass](https://github.com/safellama/plexiglass) has 153 stars, 18 forks, and 0 open issues, last pushed Feb 4, 2026. Figures are from public GitHub metadata via [autogen's repository](https://github.com/microsoft/autogen) and [plexiglass's repository](https://github.com/safellama/plexiglass). | | [autogen](/tools/microsoft-autogen.md) | [plexiglass](/tools/safellama-plexiglass.md) | | --- | --- | --- | | Tagline | A programming framework for agentic AI | A toolkit for detecting and protecting against vulnerabilities in Large Language Models (LLMs). | | Stars | 59,658 | 153 | | Forks | 8,983 | 18 | | Open issues | 945 | 0 | | 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 | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autogen](/tools/microsoft-autogen.md) | [plexiglass](/tools/safellama-plexiglass.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 87d | 157d | | Open issues (now) | 945 | 0 | | Full report | [trust report](/tools/microsoft-autogen/trust.md) | [trust report](/tools/safellama-plexiglass/trust.md) | ## Shared compatibility - **Python**: [autogen](/tools/microsoft-autogen.md) - Python runtime; [plexiglass](/tools/safellama-plexiglass.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, plexiglass is Apache-2.0. - 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 plexiglass if… - License: plexiglass is Apache-2.0, autogen is CC-BY-4.0. - Tags unique to plexiglass: adversarial-attacks, adversarial-machine-learning, cybersecurity, deep-learning. - Also covers Developer Tools. ## 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 plexiglass - Last GitHub push was 157 days ago (slowing maintenance, Feb 4, 2026). Validate activity before betting a new project on plexiglass. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - 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 plexiglass? autogen: A programming framework for agentic AI. plexiglass: A toolkit for detecting and protecting against vulnerabilities in Large Language Models (LLMs).. See the comparison table for live GitHub stats and shared categories. ### When should I choose autogen over plexiglass? Choose autogen over plexiglass when License: autogen is CC-BY-4.0, plexiglass is Apache-2.0; 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 plexiglass over autogen? Choose plexiglass over autogen when License: plexiglass is Apache-2.0, autogen is CC-BY-4.0; Tags unique to plexiglass: adversarial-attacks, adversarial-machine-learning, cybersecurity, deep-learning; Also covers Developer Tools. ### 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 plexiglass? Last GitHub push was 157 days ago (slowing maintenance, Feb 4, 2026). Validate activity before betting a new project on plexiglass. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is autogen or plexiglass more popular on GitHub? autogen has more GitHub stars (59,658 vs 153). Stars measure visibility, not whether either tool fits your constraints. ### Are autogen and plexiglass open source? Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, plexiglass: Apache-2.0). ### Where can I find alternatives to autogen or plexiglass? GraphCanon lists graph-backed alternatives at [autogen alternatives](/tools/microsoft-autogen/alternatives) and [plexiglass alternatives](/tools/safellama-plexiglass/alternatives) ([autogen markdown twin](/tools/microsoft-autogen/alternatives.md), [plexiglass markdown twin](/tools/safellama-plexiglass/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-safellama-plexiglass.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autogen or plexiglass? autogen: Steady. plexiglass: 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 plexiglass? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autogen trust report](/tools/microsoft-autogen/trust); [plexiglass trust report](/tools/safellama-plexiglass/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/_