LanceDB
This LanceDB MCP server, developed by Ryan Lisse, provides a vector database interface for AI-assisted workflows. Built with Python and leveraging FastAPI, it enables efficient storage and similarity search of vector embeddings with associated metadata. The implementation supports key operations like creating tables, adding vectors, and performing nearest neighbor searches. It integrates seamlessly with Claude Desktop and other MCP clients, allowing natural language interactions with vector data. This server is particularly useful for developers and data scientists working on applications involving semantic search, recommendation systems, or any task requiring fast similarity lookups on high-dimensional data.
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 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · 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/ryanlisse/lancedb_mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve LanceDB 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.