--- title: "moby vs langchaingo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/moby-moby-vs-tmc-langchaingo" tools: ["moby-moby", "tmc-langchaingo"] --- # moby vs langchaingo *GraphCanon updated Jul 11, 2026* ## Verdict Pick moby when license: moby is Apache-2.0, langchaingo is MIT; pick langchaingo when license: langchaingo is MIT, moby is Apache-2.0. [moby](https://mobyproject.org/) reports 72k GitHub stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 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 [moby's repository](https://github.com/moby/moby) and [langchaingo's repository](https://github.com/tmc/langchaingo). | | [moby](/tools/moby-moby.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Tagline | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | LangChain for Go, the easiest way to write LLM-based programs in Go | | Stars | 71,899 | 9,527 | | Forks | 19,126 | 1,118 | | Open issues | 3,821 | 404 | | Language | Go | Go | | Adopt for | - | LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, Inference & Serving, Developer Tools | LLM Frameworks, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [moby](/tools/moby-moby.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 1d | 180d | | Open issues (now) | 3.8k | 404 | | Owner type | Organization | User | | Security scan | No criticals | 22 low (22 low) | | Full report | [trust report](/tools/moby-moby/trust.md) | [trust report](/tools/tmc-langchaingo/trust.md) | ## 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 moby if… - License: moby is Apache-2.0, langchaingo is MIT. - Tags unique to moby: docker, containers. - Also covers Inference & Serving. - moby ships Docker support for self-hosted deployment. ### Choose langchaingo if… - License: langchaingo is MIT, moby is Apache-2.0. - Tags unique to langchaingo: ai, langchain. - - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ## When NOT to use moby - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ## 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 moby and langchaingo? moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. 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 moby over langchaingo? Choose moby over langchaingo when License: moby is Apache-2.0, langchaingo is MIT; Tags unique to moby: docker, containers; Also covers Inference & Serving; moby ships Docker support for self-hosted deployment. ### When should I choose langchaingo over moby? Choose langchaingo over moby when License: langchaingo is MIT, moby is Apache-2.0; Tags unique to langchaingo: ai, langchain; - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ### When should I avoid moby? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ### 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 moby or langchaingo more popular on GitHub? moby has more GitHub stars (71,899 vs 9,527). Stars measure visibility, not whether either tool fits your constraints. ### Are moby and langchaingo open source? Yes - both are open-source projects on GitHub (moby: Apache-2.0, langchaingo: MIT). ### Where can I find alternatives to moby or langchaingo? GraphCanon lists graph-backed alternatives at [moby alternatives](/tools/moby-moby/alternatives) and [langchaingo alternatives](/tools/tmc-langchaingo/alternatives) ([moby markdown twin](/tools/moby-moby/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/moby-moby-vs-tmc-langchaingo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, moby or langchaingo? moby: Very active. 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 moby and langchaingo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [moby trust report](/tools/moby-moby/trust); [langchaingo trust report](/tools/tmc-langchaingo/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=moby-moby`](/api/graphcanon/graph?tool=moby-moby) - 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/_