# qdrant2

> qdrant2 — neco001-qdrant2. Use this tool when you need to integrate a universal vector search server with automatic dimension detection and support for multiple OpenAI-compatible embedding APIs. It solves problems related to efficient and accurate search functionality, particularly in applications involving complex data embeddings. The qdrant2 tool accepts embedding inputs and returns relevant search results, making it ideal for use cases requiring robust and scalable search capabilities.

Canonical page: https://skillsregistry.net/skills/neco001-qdrant2  
JSON: https://api.skillsregistry.net/v1/skills/neco001-qdrant2

## Description

Universal Qdrant MCP server with automatic dimension detection and search integrity. Supports any OpenAI-compatible embedding API (OpenAI, Qwen, Gemini, Ollama).

## Trust

- **Trust score (0–1):** 0.95
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/neco001/qdrant2)

## 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": "neco001-qdrant2"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/neco001-qdrant2` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/neco001-qdrant2/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