--- title: "moby vs deep-research" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/moby-moby-vs-u14app-deep-research" tools: ["moby-moby", "u14app-deep-research"] --- # moby vs deep-research *GraphCanon updated Jul 15, 2026* ## Verdict Pick moby when moby is primarily Go; deep-research is JavaScript; pick deep-research when deep-research is primarily JavaScript; moby is Go. [moby](https://mobyproject.org/) reports 72k GitHub stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 2026. [deep-research](https://research.u14.app) has 4.6k stars, 1.1k forks, and 36 open issues, last pushed Jun 18, 2026. Figures are from public GitHub metadata via [moby's repository](https://github.com/moby/moby) and [deep-research's repository](https://github.com/u14app/deep-research). | | [moby](/tools/moby-moby.md) | [deep-research](/tools/u14app-deep-research.md) | | --- | --- | --- | | Tagline | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server. | | Stars | 71,899 | 4,632 | | Forks | 19,126 | 1,055 | | Open issues | 3,821 | 36 | | Language | Go | JavaScript | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Developer Tools, Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [moby](/tools/moby-moby.md) | [deep-research](/tools/u14app-deep-research.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 1d | 26d | | Open issues (now) | 3.8k | 36 | | Full report | [trust report](/tools/moby-moby/trust.md) | [trust report](/tools/u14app-deep-research/trust.md) | ## Choose when ### Choose moby if… - moby is primarily Go; deep-research is JavaScript. - License: moby is Apache-2.0, deep-research is MIT. - Tags unique to moby: containers, docker, go, golang. - Also covers Developer Tools. ### Choose deep-research if… - deep-research is primarily JavaScript; moby is Go. - License: deep-research is MIT, moby is Apache-2.0. - Tags unique to deep-research: anthropic, deep-research, deep-research-api, deepresearch. - Also covers Vector Databases. ## When NOT to use moby - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use deep-research - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - 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 moby and deep-research? moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. deep-research: Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.. See the comparison table for live GitHub stats and shared categories. ### When should I choose moby over deep-research? Choose moby over deep-research when moby is primarily Go; deep-research is JavaScript; License: moby is Apache-2.0, deep-research is MIT; Tags unique to moby: containers, docker, go, golang; Also covers Developer Tools. ### When should I choose deep-research over moby? Choose deep-research over moby when deep-research is primarily JavaScript; moby is Go; License: deep-research is MIT, moby is Apache-2.0; Tags unique to deep-research: anthropic, deep-research, deep-research-api, deepresearch; Also covers Vector Databases. ### When should I avoid moby? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid deep-research? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. 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 moby or deep-research more popular on GitHub? moby has more GitHub stars (71,899 vs 4,632). Stars measure visibility, not whether either tool fits your constraints. ### Are moby and deep-research open source? Yes - both are open-source projects on GitHub (moby: Apache-2.0, deep-research: MIT). ### Where can I find alternatives to moby or deep-research? GraphCanon lists graph-backed alternatives at [moby alternatives](/tools/moby-moby/alternatives) and [deep-research alternatives](/tools/u14app-deep-research/alternatives) ([moby markdown twin](/tools/moby-moby/alternatives.md), [deep-research markdown twin](/tools/u14app-deep-research/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-u14app-deep-research.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, moby or deep-research? moby: Very active. deep-research: 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 moby and deep-research? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [moby trust report](/tools/moby-moby/trust); [deep-research trust report](/tools/u14app-deep-research/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/_