--- title: "entaoai vs autogen" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/akshata29-entaoai-vs-microsoft-autogen" tools: ["akshata29-entaoai", "microsoft-autogen"] --- # entaoai vs autogen *GraphCanon updated Jul 11, 2026* ## Verdict Pick entaoai when entaoai is primarily TypeScript; autogen is Python; pick autogen when autogen is primarily Python; entaoai is TypeScript. [entaoai](https://github.com/akshata29/entaoai) reports 866 GitHub stars, 245 forks, and 12 open issues, last pushed Jan 2, 2025. [autogen](https://microsoft.github.io/autogen/) has 60k stars, 9.0k forks, and 945 open issues, last pushed Apr 15, 2026. Figures are from public GitHub metadata via [entaoai's repository](https://github.com/akshata29/entaoai) and [autogen's repository](https://github.com/microsoft/autogen). | | [entaoai](/tools/akshata29-entaoai.md) | [autogen](/tools/microsoft-autogen.md) | | --- | --- | --- | | Tagline | Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions | A programming framework for agentic AI | | Stars | 866 | 59,658 | | Forks | 245 | 8,983 | | Open issues | 12 | 945 | | Language | TypeScript | 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 | MIT | CC-BY-4.0 | | Categories | Vector Databases, LLM Frameworks | LLM Frameworks, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [entaoai](/tools/akshata29-entaoai.md) | [autogen](/tools/microsoft-autogen.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 554d | 87d | | Open issues (now) | 12 | 945 | | Owner type | User | Organization | | Full report | [trust report](/tools/akshata29-entaoai/trust.md) | [trust report](/tools/microsoft-autogen/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 entaoai if… - entaoai is primarily TypeScript; autogen is Python. - License: entaoai is MIT, autogen is CC-BY-4.0. - Tags unique to entaoai: gpt-3, azureopenai, cognitive-search, azure-webapp. - Also covers Vector Databases. ### Choose autogen if… - autogen is primarily Python; entaoai is TypeScript. - License: autogen is CC-BY-4.0, entaoai 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, ai. - Also covers AI Agents. - You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ## When NOT to use entaoai - Last GitHub push was 555 days ago (dormant maintenance, Jan 2, 2025). Validate activity before betting a new project on entaoai. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## 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. ## Common questions ### What is the difference between entaoai and autogen? entaoai: Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions. autogen: A programming framework for agentic AI. See the comparison table for live GitHub stats and shared categories. ### When should I choose entaoai over autogen? Choose entaoai over autogen when entaoai is primarily TypeScript; autogen is Python; License: entaoai is MIT, autogen is CC-BY-4.0; Tags unique to entaoai: gpt-3, azureopenai, cognitive-search, azure-webapp; Also covers Vector Databases. ### When should I choose autogen over entaoai? Choose autogen over entaoai when autogen is primarily Python; entaoai is TypeScript; License: autogen is CC-BY-4.0, entaoai 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, ai; Also covers AI Agents; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### When should I avoid entaoai? Last GitHub push was 555 days ago (dormant maintenance, Jan 2, 2025). Validate activity before betting a new project on entaoai. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### 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. ### Is entaoai or autogen more popular on GitHub? autogen has more GitHub stars (59,658 vs 866). Stars measure visibility, not whether either tool fits your constraints. ### Are entaoai and autogen open source? Yes - both are open-source projects on GitHub (entaoai: MIT, autogen: CC-BY-4.0). ### Where can I find alternatives to entaoai or autogen? GraphCanon lists graph-backed alternatives at [entaoai alternatives](/tools/akshata29-entaoai/alternatives) and [autogen alternatives](/tools/microsoft-autogen/alternatives) ([entaoai markdown twin](/tools/akshata29-entaoai/alternatives.md), [autogen markdown twin](/tools/microsoft-autogen/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/akshata29-entaoai-vs-microsoft-autogen.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, entaoai or autogen? entaoai: Dormant. autogen: 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 entaoai and autogen? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [entaoai trust report](/tools/akshata29-entaoai/trust); [autogen trust report](/tools/microsoft-autogen/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=akshata29-entaoai`](/api/graphcanon/graph?tool=akshata29-entaoai) - 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/_