# LanceDB

> LanceDB — alex-komyagin-lancedb. Use this tool when you need to interact with vector databases using natural language, enabling AI assistants to perform operations like querying, inserting, and managing vector data for applications such as similarity search, recommendation systems, or semantic analysis. It takes in natural language inputs and outputs vector data, providing a bridge between large language models and efficient vector storage. Ideal for developers and data scientists working on AI applications that require complex queries and data manipulations on large datasets.

Canonical page: https://skillsregistry.net/skills/alex-komyagin-lancedb  
JSON: https://api.skillsregistry.net/v1/skills/alex-komyagin-lancedb

## Description

This LanceDB MCP server, developed by Alex Komyagin, enables AI assistants to interact with LanceDB vector databases through natural language. It leverages the LanceDB Node.js client and Model Context Protocol to provide operations like querying, inserting, and managing vector data. Built with TypeScript and modern dependencies, it offers a bridge between large language models and efficient vector storage. The implementation is designed for developers and data scientists working on AI applications that require fast similarity search, recommendation systems, or semantic analysis on large datasets. It simplifies vector database operations for AI assistants, allowing them to perform complex queries and data manipulations using conversational language.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/alex-komyagin-lancedb)
- **Repository:** <https://github.com/adiom-data/lance-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": "alex-komyagin-lancedb"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alex-komyagin-lancedb` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alex-komyagin-lancedb/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