# LanceDB Node

> Use this tool when you need to efficiently search and retrieve similar vectors in high-dimensional spaces, solving problems such as semantic search, image similarity, and recommendation systems. The LanceDB Node takes in vector embeddings as input and outputs relevant search results, leveraging Ollama's embedding model for accurate matching. Ideal for applications requiring fast and scalable vector search capabilities, such as natural language processing, computer vision, and machine learning workflows.

Canonical page: https://skillsregistry.net/skills/vurtnec-mcp-lancedb-node  
JSON: https://api.skillsregistry.net/v1/skills/vurtnec-mcp-lancedb-node

## Description

A Node.js implementation for vector search using LanceDB and Ollama's embedding model.

## Trust

- **Trust score (0–1):** 0.95
- **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/ag91p7a1yh)
- **Repository:** <https://github.com/vurtnec/mcp-LanceDB-node>

## 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": "vurtnec-mcp-lancedb-node"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vurtnec-mcp-lancedb-node` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vurtnec-mcp-lancedb-node/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