TinyRAG

Item: TinyRAG
Rating: 67
Author: M8ven

Enables LLM agents to access a private knowledge base through MCP by automatically chunking and indexing .txt documents, with zero configuration and no Docker or vector database required.

→ spacecat398/TinyRAG-MCP · listed on glama

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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.

🔐

You'll be asked for 1 credential: OPENAI_API_KEY

These are read from process.env at runtime. Make sure you trust where they’ll be sent.

// required environment variables

This server reads these from process.env. You'll be asked to provide them before it can run.

🔐 secretOPENAI_API_KEY

configOPENAI_BASE_URL

configEMBEDDING_MODEL— text-embedding-3-small

// 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 6 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.

// embed badge in your README

[![M8ven Score](https://m8ven.ai/badge/mcp/spacecat398-tinyrag-mcp-1blzn2)](https://m8ven.ai/mcp/spacecat398-tinyrag-mcp-1blzn2)

commit: 8dd31bc658d73cccf868ceccf4e8ea361580a460

code hash: b0bde2626a2608de8de22e3bb348323622c933e1e5abe12f549769cecbb89bc0

verified: 7/13/2026, 9:51:08 AM

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