43
/ 100
1 month ago
glama
punt-quarry
Enables local semantic search over documents (PDFs, code, etc.) using local embedding models, allowing AI agents and users to find information by meaning without API keys or cloud services.
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// 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/punt-labs-quarry-17jb9q)commit: 4615d85071191c68f08fdbd813f916f983c0c228
code hash: 9a40342f1d49591f962d86b41f5f6a9e57952cad638fa3b3f0d2a6073022b7b4
verified: 6/10/2026, 11:14:09 AM