Qdrant with OpenAI Embeddings

Item: Qdrant with OpenAI Embeddings
Rating: 69
Author: M8ven

Connects AI systems to Qdrant vector databases for semantic search using OpenAI embeddings, enabling contextual document retrieval and knowledge base querying.

→ amansingh0311/mcp-qdrant-openai · listed on pulsemcp

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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 2 credentials: QDRANT_API_KEY, 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.

configQDRANT_URL— URL to your Qdrant instance (default: "http://localhost:6333")

🔐 secretQDRANT_API_KEY— Your Qdrant API key (if applicable)

🔐 secretOPENAI_API_KEY— Your OpenAI API key

// 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 5 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/amansingh0311-mcp-qdrant-openai-luri0j)](https://m8ven.ai/mcp/amansingh0311-mcp-qdrant-openai-luri0j)

commit: 1f79a9b913521938c924ccacd528ac87f3458fbe

code hash: e13cb80181add4909eb57e6968059f430c0009d994f163e8356aaba40e7500e0

verified: 7/24/2026, 8:49:56 AM

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