45
grade D
11 days ago
glama
cowork-semantic-search
Local offline semantic search over documents (txt, md, pdf, docx, pptx, csv). Indexes folders into a LanceDB vector database with multilingual embeddings and supports hybrid vector + keyword search via Reciprocal Rank Fusion. No API keys, no cloud, no Docker required.
Install from
M8ven verifies MCPs across every public registry — install directly from whichever one you prefer.
// key findings
✅
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
✅
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
// full audit trail
The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.
// improvement guidance — verified publishers only
We have 1 concrete improvement we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[](https://m8ven.ai/mcp/zhubit-cowork-semantic-search-lrs565)commit: aec520e5387411e42d893fc3f7ff5bfce2df5717
code hash: be8c391c40fd0a0fbe24ce3c7a84426bfa4de3e9c9e36e3ddce5037957fa5e97
verified: 4/11/2026, 2:28:50 PM