# qdrant-mcp

> Use this tool when you need to perform semantic search on documents or ingest local files for intelligent information retrieval. It solves problems related to document management, search, and filtering by enabling vector search with metadata filters and generating embeddings with OpenAI. The tool takes in local documents and outputs searchable data with relevant embeddings and metadata.

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

## Description

MCP server for document ingestion and semantic search on Qdrant. Enables ingesting local documents, generating embeddings with OpenAI, and performing vector search with metadata filters.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/rqvr42jogy)
- **Repository:** <https://github.com/msstnk/qdrant-mcp>

## 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": "msstnk-qdrant-mcp"
    }
  }
}
```

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