--- title: "autogen vs langchaingo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-autogen-vs-tmc-langchaingo" tools: ["microsoft-autogen", "tmc-langchaingo"] --- # autogen vs langchaingo *GraphCanon updated Jul 11, 2026* ## Verdict Pick autogen if 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; pick langchaingo if langChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. [autogen](https://microsoft.github.io/autogen/) reports 60k GitHub stars, 9.0k forks, and 945 open issues, last pushed Apr 15, 2026. [langchaingo](https://tmc.github.io/langchaingo/) has 9.5k stars, 1.1k forks, and 404 open issues, last pushed Jan 11, 2026. Figures are from public GitHub metadata via [autogen's repository](https://github.com/microsoft/autogen) and [langchaingo's repository](https://github.com/tmc/langchaingo). | | [autogen](/tools/microsoft-autogen.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Tagline | A programming framework for agentic AI | LangChain for Go, the easiest way to write LLM-based programs in Go | | Stars | 59,658 | 9,527 | | Forks | 8,983 | 1,118 | | Open issues | 945 | 404 | | Language | Python | Go | | 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. | LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. | | Persona | - | - | | Runtime | - | - | | License | CC-BY-4.0 | MIT | | Categories | LLM Frameworks, AI Agents | LLM Frameworks, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autogen](/tools/microsoft-autogen.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 87d | 180d | | Open issues (now) | 945 | 404 | | Owner type | Organization | User | | Security scan | No lockfile | 22 low (22 low) | | Full report | [trust report](/tools/microsoft-autogen/trust.md) | [trust report](/tools/tmc-langchaingo/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. ## Decision facts: langchaingo - **Adopt for:** LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. ## Choose when ### Choose autogen if… - autogen is primarily Python; langchaingo is Go. - License: autogen is CC-BY-4.0, langchaingo 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 langchaingo if… - langchaingo is primarily Go; autogen is Python. - License: langchaingo is MIT, autogen is CC-BY-4.0. - Tags unique to langchaingo: go, langchain, golang. - Also covers Developer Tools. - - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ## 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 langchaingo - - If your project strictly adheres to another programming language where other implementations of LangChain are available. - - When your application requires heavy customization at the framework level that might not be directly supported within LangChainGo’s current implementation. ## Common questions ### What is the difference between autogen and langchaingo? autogen: A programming framework for agentic AI. langchaingo: LangChain for Go, the easiest way to write LLM-based programs in Go. See the comparison table for live GitHub stats and shared categories. ### When should I choose autogen over langchaingo? Choose autogen over langchaingo when autogen is primarily Python; langchaingo is Go; License: autogen is CC-BY-4.0, langchaingo 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 langchaingo over autogen? Choose langchaingo over autogen when langchaingo is primarily Go; autogen is Python; License: langchaingo is MIT, autogen is CC-BY-4.0; Tags unique to langchaingo: go, langchain, golang; Also covers Developer Tools; - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ### 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 langchaingo? - If your project strictly adheres to another programming language where other implementations of LangChain are available. - When your application requires heavy customization at the framework level that might not be directly supported within LangChainGo’s current implementation. ### Is autogen or langchaingo more popular on GitHub? autogen has more GitHub stars (59,658 vs 9,527). Stars measure visibility, not whether either tool fits your constraints. ### Are autogen and langchaingo open source? Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, langchaingo: MIT). ### Where can I find alternatives to autogen or langchaingo? GraphCanon lists graph-backed alternatives at [autogen alternatives](/tools/microsoft-autogen/alternatives) and [langchaingo alternatives](/tools/tmc-langchaingo/alternatives) ([autogen markdown twin](/tools/microsoft-autogen/alternatives.md), [langchaingo markdown twin](/tools/tmc-langchaingo/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-tmc-langchaingo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autogen or langchaingo? autogen: Steady. langchaingo: 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 langchaingo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autogen trust report](/tools/microsoft-autogen/trust); [langchaingo trust report](/tools/tmc-langchaingo/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/_