# mcp-server-qdrant

> Use this tool when you need to efficiently store and retrieve memories based on semantic similarity, leveraging Qdrant's vector search capabilities to enable advanced memory retrieval and management. It solves problems related to information retrieval, knowledge management, and semantic search, providing a robust interface for storing and querying memories. Ideal for applications requiring intelligent memory layers, such as AI models, chatbots, or knowledge graphs.

Canonical page: https://skillsregistry.net/skills/ai-integr8tor-mcp-server-qdrant  
JSON: https://api.skillsregistry.net/v1/skills/ai-integr8tor-mcp-server-qdrant

## Description

An MCP server for storing and retrieving memories using Qdrant vector search, acting as a semantic memory layer.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/dt884bt9gf)
- **Repository:** <https://github.com/ai-integr8tor/mcp-server-qdrant>

## 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": "ai-integr8tor-mcp-server-qdrant"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-integr8tor-mcp-server-qdrant` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-integr8tor-mcp-server-qdrant/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