# Qdrant MCP Server

> Use this tool when you need to efficiently store, search, and manage dense vectors, such as those generated by machine learning models, and automatically embed text data for semantic search and retrieval. It solves problems related to similarity search, clustering, and data retrieval in various applications, including natural language processing and computer vision. The Qdrant MCP Server accepts vector data and text inputs, and outputs relevant search results and vector representations.

Canonical page: https://skillsregistry.net/skills/jimmy974-qdrant-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/jimmy974-qdrant-mcp-server

## Description

Enables interaction with Qdrant vector database for storing, searching, and managing vectors with automatic text embedding.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mk6hcj9q3o)
- **Repository:** <https://github.com/Jimmy974/qdrant-mcp-server>

## 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": "jimmy974-qdrant-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jimmy974-qdrant-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jimmy974-qdrant-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt