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Search documents and code semantically with local embeddings, no cloud or API keys.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "punt-quarry" yet — see the docs or source repo.
Run a semantic search over this local codebase and find files, functions, and notes related to user permission checks and role-based access control, then rank and summarize them by relevance.
A ranked list of relevant code files, function snippets, and explanations, plus a brief summary.
Search the local PDF documents for content semantically closest to refund policy exceptions, list the matching passages and page numbers, and distill them into three key points.
Relevant PDF passages with page references and a distilled set of key takeaways.
Using the locally indexed documents, notes, and code, perform semantic search on how the system handles offline cache sync conflicts and prepare a direct answer.
A grounded answer based on local materials, with supporting references for the conclusion.
Safely let agents access Postgres, MySQL, and Redis with read-only defaults.
Connect to Qdrant for semantic search and document relationship analysis.
Index codebases into Qdrant for semantic code search and faster AI retrieval.
Store and query vector data through a unified Qdrant semantic search interface.
Search Markdown knowledge bases, notes, and docs to quickly find needed information.
Search and retrieve knowledge base documents with Qdrant hybrid retrieval.