RagDocs MCP Server

Enables semantic search and management of documentation through vector similarity using Qdrant and Ollama/OpenAI embeddings.

→ mcpflow/ragdocs · listed on glama

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// key findings

⚠️

Known vulnerabilities in dependencies: 17 high

Affects packages this MCP installs at runtime. Upgrade or remove the affected dependency.

✅

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.

🔐

You'll be asked for 2 credentials: OPENAI_API_KEY, QDRANT_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.

configEMBEDDING_PROVIDER— "": "ollama"

🔐 secretOPENAI_API_KEY— "": "your-api-key"

🔐 secretQDRANT_API_KEY— "": "your-qdrant-api-key",

configQDRANT_URL— "": "http://127.0.0.1:6333",

// 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/mcpflow-ragdocs-8cdt8o)](https://m8ven.ai/mcp/mcpflow-ragdocs-8cdt8o)

commit: 49101ee600ec9365becd8efb4d97e92edf88f439

code hash: 14118d82782c215a7e02fa0db404c64a5c3699088dc53473e37f5292515d6c15

verified: 6/16/2026, 1:24:29 PM

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