# Qdrant Retrieve

> Use this tool when you need to retrieve semantically similar documents across multiple collections using natural language queries, enabling AI assistants to find relevant information beyond exact keyword matching. It solves problems in knowledge retrieval workflows where semantic understanding is crucial, and accepts natural language queries as input, returning a list of similar documents as output. Ideal for use cases where contextual relevance is more important than exact keyword search results.

Canonical page: https://skillsregistry.net/skills/gergelyszerovay-qdrant-retrieve  
JSON: https://api.skillsregistry.net/v1/skills/gergelyszerovay-qdrant-retrieve

## Description

An MCP server that enables semantic search capabilities through Qdrant vector database integration. It allows AI assistants to retrieve semantically similar documents across multiple collections using natural language queries, with configurable result counts and collection source tracking. The server supports both stdio and HTTP transports, includes REST API endpoints with OpenAPI documentation, and uses embedding models like Xenova/all-MiniLM-L6-v2 to generate vector representations for similarity matching. Particularly useful for knowledge retrieval workflows where semantic understanding is more important than exact keyword matching.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/gergelyszerovay-qdrant-retrieve)
- **Repository:** <https://github.com/gergelyszerovay/mcp-server-qdrant-retrieve>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "gergelyszerovay-qdrant-retrieve"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gergelyszerovay-qdrant-retrieve` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gergelyszerovay-qdrant-retrieve/pull`

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