--- title: "deep-research vs osgrep" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dzhng-deep-research-vs-ryandonofrio3-osgrep" tools: ["dzhng-deep-research", "ryandonofrio3-osgrep"] --- # deep-research vs osgrep *GraphCanon updated Sep 20, 2026* ## Verdict Pick deep-research if deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics; pick osgrep if osgrep is an open-source tool focused on semantic search capabilities specifically designed for integration with AI agents using TypeScript. [deep-research](https://github.com/dzhng/deep-research) reports 20k GitHub stars, 2.0k forks, and 93 open issues, last pushed Apr 11, 2026. [osgrep](https://github.com/Ryandonofrio3/osgrep) has 1.1k stars, 67 forks, and 21 open issues, last pushed Jan 17, 2026. Figures are from public GitHub metadata via [deep-research's repository](https://github.com/dzhng/deep-research) and [osgrep's repository](https://github.com/Ryandonofrio3/osgrep). | | [deep-research](/tools/dzhng-deep-research.md) | [osgrep](/tools/ryandonofrio3-osgrep.md) | | --- | --- | --- | | Tagline | An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models. | Open Source Semantic Search for your AI Agent | | Stars | 19,571 | 1,145 | | Forks | 1,993 | 67 | | Open issues | 93 | 21 | | Language | TypeScript | TypeScript | | Adopt for | Deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics. | osgrep is an open-source tool focused on semantic search capabilities specifically designed for integration with AI agents using TypeScript. | | Persona | - | - | | Runtime | - | - | | License | MIT | osgrep is available under the Apache-2.0 license, offering permissive use for both commercial and non-commercial projects without requiring derivative works to be open-sourced. | | Categories | AI Agents, Data & Retrieval | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deep-research](/tools/dzhng-deep-research.md) | [osgrep](/tools/ryandonofrio3-osgrep.md) | | --- | --- | --- | | Days since push | 129d | 245d | | Open issues (now) | 93 | 21 | | Stars delta | +195 (30d) | +5 (30d) | | Open issues delta | +3 (30d) | 0 (30d) | | Full report | [trust report](/tools/dzhng-deep-research/trust.md) | [trust report](/tools/ryandonofrio3-osgrep/trust.md) | ## Shared compatibility - **Node.js**: [deep-research](/tools/dzhng-deep-research.md) - Node.js runtime; [osgrep](/tools/ryandonofrio3-osgrep.md) - Node.js runtime ## Decision facts: deep-research - **Requirements:** Requires Docker - **Adopt for:** Deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics. ## Decision facts: osgrep - **Adopt for:** osgrep is an open-source tool focused on semantic search capabilities specifically designed for integration with AI agents using TypeScript. - **License detail:** osgrep is available under the Apache-2.0 license, offering permissive use for both commercial and non-commercial projects without requiring derivative works to be open-sourced. ## Choose when ### Choose deep-research if… - License: deep-research is MIT, osgrep is Apache-2.0. - Requirements: Requires Docker. - Tags unique to deep-research: agent, ai, gpt, o3-mini. - Also covers AI Agents. - deep-research ships Docker support for self-hosted deployment. - When you need a tool that can refine its topic focus over time through repeated iterations. ### Choose osgrep if… - License: osgrep is Apache-2.0, deep-research is MIT. - Tags unique to osgrep: colbert, embeddings, grep-search. - osgrep ships an MCP server manifest. - - You need advanced semantic search functionality tailored to work seamlessly with your AI agent. ## When NOT to use deep-research - When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment. - If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys. ## When NOT to use osgrep - - If your search requirements can be met with simple keyword matching rather than semantic analysis, as osgrep specializes in more complex semantic searches. - - Your AI project is not using TypeScript or where seamless integration with TypeScript-specific features of osgrep would offer no advantage. - - You require additional proprietary functionalities that go beyond what the open-source license and community provide. ## Common questions ### What is the difference between deep-research and osgrep? deep-research: An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.. osgrep: Open Source Semantic Search for your AI Agent. See the comparison table for live GitHub stats and shared categories. ### When should I choose deep-research over osgrep? Choose deep-research over osgrep when License: deep-research is MIT, osgrep is Apache-2.0; Requirements: Requires Docker; Tags unique to deep-research: agent, ai, gpt, o3-mini; Also covers AI Agents; deep-research ships Docker support for self-hosted deployment; When you need a tool that can refine its topic focus over time through repeated iterations. ### When should I choose osgrep over deep-research? Choose osgrep over deep-research when License: osgrep is Apache-2.0, deep-research is MIT; Tags unique to osgrep: colbert, embeddings, grep-search; osgrep ships an MCP server manifest; - You need advanced semantic search functionality tailored to work seamlessly with your AI agent. ### When should I avoid deep-research? When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment. If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys. ### When should I avoid osgrep? - If your search requirements can be met with simple keyword matching rather than semantic analysis, as osgrep specializes in more complex semantic searches. - Your AI project is not using TypeScript or where seamless integration with TypeScript-specific features of osgrep would offer no advantage. - You require additional proprietary functionalities that go beyond what the open-source license and community provide. ### Is deep-research or osgrep more popular on GitHub? deep-research has more GitHub stars (19,571 vs 1,145). Stars measure visibility, not whether either tool fits your constraints. ### Are deep-research and osgrep open source? Yes - both are open-source projects on GitHub (deep-research: MIT, osgrep: Apache-2.0). ### Where can I find alternatives to deep-research or osgrep? GraphCanon lists graph-backed alternatives at [deep-research alternatives](/tools/dzhng-deep-research/alternatives) and [osgrep alternatives](/tools/ryandonofrio3-osgrep/alternatives) ([deep-research markdown twin](/tools/dzhng-deep-research/alternatives.md), [osgrep markdown twin](/tools/ryandonofrio3-osgrep/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/dzhng-deep-research-vs-ryandonofrio3-osgrep.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deep-research or osgrep? deep-research: Slowing. osgrep: 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 deep-research and osgrep? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deep-research trust report](/tools/dzhng-deep-research/trust); [osgrep trust report](/tools/ryandonofrio3-osgrep/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dzhng-deep-research`](/api/graphcanon/graph?tool=dzhng-deep-research) - 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/_