FAQ RAG MCP Server

Enables semantic search and question-answering over FAQ documents using RAG (Retrieval-Augmented Generation) with OpenAI embeddings and in-memory vector similarity.

→ rhamsagar-sf/rag-mcp-project · 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— export =sk-...

configFAQ_DIR

configEMBED_MODEL— export =text-embedding-ada-002

configLLM_MODEL— export =gpt-3.5-turbo

configCHUNK_SIZE

configTOP_K_DEFAULT

configSIMILARITY_THRESHOLD

// 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 4 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/rhamsagar-sf-rag-mcp-project-wx7yf4)](https://m8ven.ai/mcp/rhamsagar-sf-rag-mcp-project-wx7yf4)

commit: 8bc2ea9bd4648ab0a0b3330f53c1f9791d43adf6

code hash: 47599983352fa0d77b7ca0d6921fd8c0bc6f39c389ed256e7cfc85e4adc08a1d

verified: 6/26/2026, 9:47:51 AM

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