Qdrant Knowledge Graph
This MCP server, developed by Jarad DeLorenzo, provides a knowledge graph implementation with semantic search capabilities powered by Qdrant vector database. Built with TypeScript and leveraging the Model Context Protocol SDK, it offers tools for managing entities, relations, and observations in a graph structure. The implementation focuses on efficient storage and retrieval, using both file-based persistence and Qdrant for vector search. It's particularly useful for applications requiring structured knowledge representation with semantic querying, enabling use cases such as intelligent information retrieval, relationship analysis, and context-aware AI interactions without directly dealing with complex graph database operations.
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 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/delorenj/mcp-qdrant-memory
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve Qdrant Knowledge Graph 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.