--- title: "cherche vs osgrep" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/raphaelsty-cherche-vs-ryandonofrio3-osgrep" tools: ["raphaelsty-cherche", "ryandonofrio3-osgrep"] --- # cherche vs osgrep *GraphCanon updated Aug 23, 2026* ## Verdict Pick cherche if cherche is a Python library for implementing neural search capabilities; pick osgrep if osgrep is an open-source tool focused on semantic search capabilities specifically designed for integration with AI agents using TypeScript. [cherche](https://github.com/raphaelsty/cherche) reports 332 GitHub stars, 14 forks, and 4 open issues, last pushed Jun 1, 2024. [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 [cherche's repository](https://github.com/raphaelsty/cherche) and [osgrep's repository](https://github.com/Ryandonofrio3/osgrep). | | [cherche](/tools/raphaelsty-cherche.md) | [osgrep](/tools/ryandonofrio3-osgrep.md) | | --- | --- | --- | | Tagline | Neural Search | Open Source Semantic Search for your AI Agent | | Stars | 332 | 1,139 | | Forks | 14 | 67 | | Open issues | 4 | 21 | | Language | Python | TypeScript | | Adopt for | Cherche is a Python library for implementing neural search capabilities. | 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 | Data & Retrieval, Evaluation & Observability, Vector Databases | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [cherche](/tools/raphaelsty-cherche.md) | [osgrep](/tools/ryandonofrio3-osgrep.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 812d | 216d | | Open issues (now) | 4 | 21 | | Stars delta | 0 (30d) | -1 (30d) | | Full report | [trust report](/tools/raphaelsty-cherche/trust.md) | [trust report](/tools/ryandonofrio3-osgrep/trust.md) | ## Decision facts: cherche - **Adopt for:** Cherche is a Python library for implementing neural search capabilities. ## 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 cherche if… - cherche is primarily Python; osgrep is TypeScript. - License: cherche is MIT, osgrep is Apache-2.0. - Tags unique to cherche: bm25, flashtext, information-retrieval, machine-learning. - Also covers Evaluation & Observability, Vector Databases. - Cherche is a Python library for implementing neural search capabilities. ### Choose osgrep if… - osgrep is primarily TypeScript; cherche is Python. - License: osgrep is Apache-2.0, cherche 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 cherche - Last GitHub push was 815 days ago (dormant maintenance, Jun 1, 2024). Validate activity before betting a new project on cherche. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## 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 cherche and osgrep? cherche: Neural Search. osgrep: Open Source Semantic Search for your AI Agent. See the comparison table for live GitHub stats and shared categories. ### When should I choose cherche over osgrep? Choose cherche over osgrep when cherche is primarily Python; osgrep is TypeScript; License: cherche is MIT, osgrep is Apache-2.0; Tags unique to cherche: bm25, flashtext, information-retrieval, machine-learning; Also covers Evaluation & Observability, Vector Databases; Cherche is a Python library for implementing neural search capabilities. ### When should I choose osgrep over cherche? Choose osgrep over cherche when osgrep is primarily TypeScript; cherche is Python; License: osgrep is Apache-2.0, cherche 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 cherche? Last GitHub push was 815 days ago (dormant maintenance, Jun 1, 2024). Validate activity before betting a new project on cherche. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### 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 cherche or osgrep more popular on GitHub? osgrep has more GitHub stars (1,139 vs 332). Stars measure visibility, not whether either tool fits your constraints. ### Are cherche and osgrep open source? Yes - both are open-source projects on GitHub (cherche: MIT, osgrep: Apache-2.0). ### Where can I find alternatives to cherche or osgrep? GraphCanon lists graph-backed alternatives at [cherche alternatives](/tools/raphaelsty-cherche/alternatives) and [osgrep alternatives](/tools/ryandonofrio3-osgrep/alternatives) ([cherche markdown twin](/tools/raphaelsty-cherche/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/raphaelsty-cherche-vs-ryandonofrio3-osgrep.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, cherche or osgrep? cherche: Dormant. 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 cherche and osgrep? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [cherche trust report](/tools/raphaelsty-cherche/trust); [osgrep trust report](/tools/ryandonofrio3-osgrep/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=raphaelsty-cherche`](/api/graphcanon/graph?tool=raphaelsty-cherche) - 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/_