--- title: "autogen vs llms-tools" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-autogen-vs-petroivaniuk-llms-tools" tools: ["microsoft-autogen", "petroivaniuk-llms-tools"] --- # autogen vs llms-tools *GraphCanon updated Jul 11, 2026* ## Verdict Pick autogen when license: autogen is CC-BY-4.0, llms-tools is Apache-2.0; pick llms-tools when license: llms-tools 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. [llms-tools](https://github.com/PetroIvaniuk/llms-tools) has 319 stars, 46 forks, and 3 open issues, last pushed Jun 1, 2026. Figures are from public GitHub metadata via [autogen's repository](https://github.com/microsoft/autogen) and [llms-tools's repository](https://github.com/PetroIvaniuk/llms-tools). | | [autogen](/tools/microsoft-autogen.md) | [llms-tools](/tools/petroivaniuk-llms-tools.md) | | --- | --- | --- | | Tagline | A programming framework for agentic AI | A list of LLMs Tools & Projects | | Stars | 59,658 | 319 | | Forks | 8,983 | 46 | | Open issues | 945 | 3 | | Language | 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 | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autogen](/tools/microsoft-autogen.md) | [llms-tools](/tools/petroivaniuk-llms-tools.md) | | --- | --- | --- | | Days since push | 87d | 39d | | Open issues (now) | 945 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/microsoft-autogen/trust.md) | [trust report](/tools/petroivaniuk-llms-tools/trust.md) | ## 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, llms-tools 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, autogen, autogen-ecosystem. - Also covers AI Agents. - You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### Choose llms-tools if… - License: llms-tools is Apache-2.0, autogen is CC-BY-4.0. - Tags unique to llms-tools: chat-bot, chatbots, data-science, llm. - Also covers Evaluation & Observability. ## 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 llms-tools - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - 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 llms-tools? autogen: A programming framework for agentic AI. llms-tools: A list of LLMs Tools & Projects. See the comparison table for live GitHub stats and shared categories. ### When should I choose autogen over llms-tools? Choose autogen over llms-tools when License: autogen is CC-BY-4.0, llms-tools 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, autogen, autogen-ecosystem; 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 llms-tools over autogen? Choose llms-tools over autogen when License: llms-tools is Apache-2.0, autogen is CC-BY-4.0; Tags unique to llms-tools: chat-bot, chatbots, data-science, llm; Also covers Evaluation & Observability. ### 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 llms-tools? Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is autogen or llms-tools more popular on GitHub? autogen has more GitHub stars (59,658 vs 319). Stars measure visibility, not whether either tool fits your constraints. ### Are autogen and llms-tools open source? Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, llms-tools: Apache-2.0). ### Where can I find alternatives to autogen or llms-tools? GraphCanon lists graph-backed alternatives at [autogen alternatives](/tools/microsoft-autogen/alternatives) and [llms-tools alternatives](/tools/petroivaniuk-llms-tools/alternatives) ([autogen markdown twin](/tools/microsoft-autogen/alternatives.md), [llms-tools markdown twin](/tools/petroivaniuk-llms-tools/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-petroivaniuk-llms-tools.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autogen or llms-tools? autogen: Steady. llms-tools: Steady. 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 llms-tools? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autogen trust report](/tools/microsoft-autogen/trust); [llms-tools trust report](/tools/petroivaniuk-llms-tools/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/_