{"data":{"slug":"yoanbernabeu-grepai","name":"grepai","tagline":"Semantic Search & Call Graphs for AI Agents (100% Local)","github_url":"https://github.com/yoanbernabeu/grepai","owner":"yoanbernabeu","repo":"grepai","owner_avatar_url":"https://avatars.githubusercontent.com/u/59195351?v=4","primary_language":"C","stars":1825,"forks":152,"topics":["ai","claude-code","cli","code-search","cursor","developer-tools","embeddings","golang","mcp","privacy-first","semantic-search","vector-search"],"archived":false,"github_pushed_at":"2026-06-22T05:34:29+00:00","maintenance_label":"Steady","stars_delta_30d":36,"url":"https://www.graphcanon.com/tools/yoanbernabeu-grepai","markdown_url":"https://www.graphcanon.com/tools/yoanbernabeu-grepai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/yoanbernabeu-grepai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=yoanbernabeu-grepai","description":"Semantic Search & Call Graphs for AI Agents (100% Local)","homepage_url":"https://yoanbernabeu.github.io/grepai/","license":"MIT","open_issues":97,"watchers":11,"ai_summary":"A tool for developing local semantic search and call graphs targeted at AI agents with focus on privacy first","readme_excerpt":"## Installation\n\n**Homebrew (macOS):**\n```bash\nbrew install yoanbernabeu/tap/grepai\n```\n\n**Linux/macOS:**\n```bash\ncurl -sSL https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.sh | sh\n```\n\n**Windows (PowerShell):**\n```powershell\nirm https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.ps1 | iex\n```\n\nRequires an embedding provider — [Ollama](https://ollama.ai) (default), [LM Studio](https://lmstudio.ai), or OpenAI.\n\n**Ollama (recommended):**\n```bash\nollama pull nomic-embed-text\n```\n\n---\n\n## Quick Start\n\n```bash\ngrepai init                        # Initialize in your project\ngrepai watch                       # Start indexing daemon\ngrepai search \"error handling\"     # Search semantically\ngrepai trace callers \"Login\"       # Find who calls a function\n```\n\n---\n\n## License\n\n[MIT License](LICENSE) - Yoan Bernabeu 2026","github_created_at":"2026-01-09T13:01:33+00:00","created_at":"2026-07-11T11:30:17.280996+00:00","updated_at":"2026-08-22T12:00:59.581649+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"claude-code","name":"claude-code"},{"slug":"cli","name":"cli"},{"slug":"code-search","name":"code-search"},{"slug":"cursor","name":"cursor"},{"slug":"embeddings","name":"embeddings"},{"slug":"mcp","name":"mcp"},{"slug":"privacy-first","name":"privacy-first"}],"trust":{"provenance":{"is_fork":false,"github_id":1131085323,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-22T12:00:58.882Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":0,"days_since_push":61,"last_release_at":"2026-03-16T05:53:04Z","stars_delta_30d":36,"open_issues_delta_30d":1},"security_summary":{"status":"no_manifest","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:30:18.475Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-22T12:00:59.313Z"},"languages":{"value":["c"],"source":"github.language","observed_at":"2026-08-22T12:00:59.313Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-22T12:00:59.313Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"Available at no cost due to its MIT licensing, with the scope of use limited only by any dependencies it requires."},"requirements":{"min_ram_gb":null,"requires_docker":false},"constraints":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"when_to_use":["When you need to develop a system that prioritizes local processing without cloud dependencies, which is essential in highly regulated environments where data privacy and security are paramount.","If your project benefits from having detailed code-level insights through call graphs that help in understanding and maintaining complex AI agent systems."],"when_not_to_use":["Not suitable if your application requires real-time updates from cloud-based services, as grepai operates entirely locally without any online components for updating its functionality.","If the development team prefers not to deal with C language implementation details,grepai might be less attractive given that other tools may support more modern or higher-level languages like Python."],"source":"enrich:decision_facts","observed_at":"2026-07-14T20:13:17.052Z"},"constraint_facets":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - Available at no cost due to its MIT licensing, with the scope of use limited only by any dependencies it requires."},{"label":"Adopt for","value":"grepai is designed for developing local semantic search and call graphs for AI agents with an emphasis on privacy."},{"label":"License detail","value":"MIT license, allowing for wide usage in both open-source and proprietary applications without restrictions on redistribution."}]}}