{"repo":"ZhuBit/cowork-semantic-search","free":true,"listed":false,"github":"https://github.com/ZhuBit/cowork-semantic-search","clone":"git clone https://github.com/ZhuBit/cowork-semantic-search.git","description":null,"language":"Python","stars":28,"topics":["claude-code","document-search","lancedb","mcp","mcp-server","obsidian","offline","rag","semantic-search","vector-search"],"license":"AGPL-3.0","category":"mcp-servers","readme_excerpt":"cowork-semantic-search If you find this useful, consider giving it a ⭐ — it helps others discover the project. Local semantic search for your documents. No API keys. No cloud. Works with any MCP client. --- Why AI coding tools are powerful, but they have blind spots when it comes to your local files: - Frozen knowledge -- training data has a cutoff. Your latest reports, notes, and contracts don't exist in the model's world. - Context window limits -- you can't paste 500 documents into a prompt. - No cross-file search -- your AI tool can read one file at a time, but can't search across your entire document library for the relevant pieces. This plugin bridges that gap. It indexes your local documents into a small, fast vector database. When you ask a question, it retrieves only the relevant pieces -- so your AI tool can answer with your actual data. Features - Fully offline -- one-time model download ( 120MB), then no network calls. No data leaves your machine. - Incremental indexing -- SHA-256 content hashing. Only changed files get reprocessed. Re-indexing 1000 files where 3 changed takes seconds. - Multilingual -- handles 50+ languages natively. Search in one language, find results in another. - Hybrid search -- combines semantic similarity with full-text keyword search via Reciprocal Rank Fusion. Catches what pure vector search misses. - Multiple formats -- txt, md, pdf, docx, pptx, csv out of the box. - Any MCP client -- works with Claude Code, Cursor, Windsurf, Cline, and","default_branch":null,"files":null,"tree":[],"storefront":"/r/ZhuBit","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ZhuBit/cowork-semantic-search/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}