Qdrant Vector Database
MCP-Qdrant Server provides a vector database integration for AI assistants, combining a Qdrant vector database with a specialized server that enables knowledge storage and retrieval. The implementation uses Docker containers to run both the Qdrant database and the MCP server, with the server utilizing the sentence-transformers embedding model to convert natural language into vector representations. It exposes two primary tools: one for storing code snippets with natural language descriptions, and another for searching the knowledge base using semantic queries. This setup is particularly useful for AI assistants that need to maintain persistent memory of code examples and technical knowledge across conversations.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Qdrant Vector Database from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp --scope user for --scope project to commit it to .mcp.json.