--- title: "autogen vs automem" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-autogen-vs-verygoodplugins-automem" tools: ["microsoft-autogen", "verygoodplugins-automem"] --- # autogen vs automem *GraphCanon updated Jul 11, 2026* ## Verdict Pick autogen when license: autogen is CC-BY-4.0, automem is MIT; pick automem when license: automem 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. [automem](https://automem.ai/) has 777 stars, 98 forks, and 12 open issues, last pushed Jul 7, 2026. Figures are from public GitHub metadata via [autogen's repository](https://github.com/microsoft/autogen) and [automem's repository](https://github.com/verygoodplugins/automem). | | [autogen](/tools/microsoft-autogen.md) | [automem](/tools/verygoodplugins-automem.md) | | --- | --- | --- | | Tagline | A programming framework for agentic AI | AutoMem is a graph-vector memory service that gives AI assistants durable, relational memory: | | Stars | 59,658 | 777 | | Forks | 8,983 | 98 | | Open issues | 945 | 12 | | 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 | LLM Frameworks, AI Agents | LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autogen](/tools/microsoft-autogen.md) | [automem](/tools/verygoodplugins-automem.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 87d | 3d | | Open issues (now) | 945 | 12 | | Full report | [trust report](/tools/microsoft-autogen/trust.md) | [trust report](/tools/verygoodplugins-automem/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, automem 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: llm-framework, autogen, agents, agentic-agi. - Also covers AI Agents. - You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### Choose automem if… - License: automem is MIT, autogen is CC-BY-4.0. - Tags unique to automem: memory, qdrant, falkordb, llm. - Also covers Vector Databases. ## 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 automem - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between autogen and automem? autogen: A programming framework for agentic AI. automem: AutoMem is a graph-vector memory service that gives AI assistants durable, relational memory:. See the comparison table for live GitHub stats and shared categories. ### When should I choose autogen over automem? Choose autogen over automem when License: autogen is CC-BY-4.0, automem 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: llm-framework, autogen, agents, agentic-agi; 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 automem over autogen? Choose automem over autogen when License: automem is MIT, autogen is CC-BY-4.0; Tags unique to automem: memory, qdrant, falkordb, llm; Also covers Vector Databases. ### 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 automem? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is autogen or automem more popular on GitHub? autogen has more GitHub stars (59,658 vs 777). Stars measure visibility, not whether either tool fits your constraints. ### Are autogen and automem open source? Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, automem: MIT). ### Where can I find alternatives to autogen or automem? GraphCanon lists graph-backed alternatives at [autogen alternatives](/tools/microsoft-autogen/alternatives) and [automem alternatives](/tools/verygoodplugins-automem/alternatives) ([autogen markdown twin](/tools/microsoft-autogen/alternatives.md), [automem markdown twin](/tools/verygoodplugins-automem/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-verygoodplugins-automem.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autogen or automem? autogen: Steady. automem: 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 automem? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autogen trust report](/tools/microsoft-autogen/trust); [automem trust report](/tools/verygoodplugins-automem/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/_