• SCHEMA
  • STORAGE
  • AUDIT
  • HUMAN

How to provision vector tables with your AI

Connect LanceDB to your AI client once. From there, you can manage your vector database schemas through simple conversation.

Ask AI about this page

Short answer

How can I create vector tables using my AI?

You describe the schema and table requirements in chat, and your AI uses the LanceDB MCP to build the table for you. This lets you set up columnar storage for multi-modal data without writing manual database commands. You'll get structured tables ready for vector search immediately.

The results of your request

Where your data lands

What happens after you send your prompt.

SCHEMA

Structured tables

Your AI defines the Apache Arrow schema based on your description. You get a ready-to-use columnar table for your data.

STORAGE

Serverless setup

The AI provisions the table in a serverless environment. You don't have to manage any underlying infrastructure.

AUDIT

Table inventory

The AI can check your existing database state. You'll know exactly which tables are currently active and available.

HUMAN

Manual review

You decide if the schema matches your multi-modal needs. The AI proposes the structure, but you confirm the final setup.

The workflow

What your AI does when the request arrives.

The AI translates your natural language into database operations.

  1. Analyze requirements

    Your AI parses your chat message to identify the necessary columns and data types for your multi-modal workload.

    list_tables

  2. Verify existing data

    The AI checks your current database to ensure there are no naming conflicts or existing tables with the same name.

    list_tables

  3. Build the table

    The AI executes the command to create a new columnar table using the specified Apache Arrow schema.

    create_table

  4. Confirm success

    The AI verifies the new table exists and reports back to you that the provisioning is complete.

    list_tables

Try it

Copy these to start.

Use these prompts to begin provisioning your data.

Starting points

Swap out the table names and column types to match your specific data needs.

LanceDB Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_85lSO635ajE8lXHCZKWQ7UC6VHfybBdy20nU97wm/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — LanceDB capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "lancedb-serverless-vector-db-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_85lSO635ajE8lXHCZKWQ7UC6VHfybBdy20nU97wm/mcp"
    }
  }
}
Copy into chat04

  • Create a new LanceDB table named 'image_embeddings' with a vector column for 512-dimensional embeddings.

  • List all the tables currently in my LanceDB instance.

  • Set up a columnar table called 'sensor_data' with float and timestamp columns for my multi-modal project.

  • Check if a table named 'user_profiles' already exists in the database.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect LanceDB once, then ask.

Just click to connect. Your credentials stay encrypted, and you can immediately start managing your vector tables through your preferred AI client.

Connect LanceDB to your AI

FAQ

How this task behaves

  • 01

    Can the AI delete my existing tables?

    No. The AI only has tools to create and list tables. It cannot delete or drop any existing data.

  • 02

    Do I need to provide the Apache Arrow schema manually?

    No. You can describe the columns and types in plain English, and the AI will generate the schema for you.

  • 03

    Can the AI modify the schema of a table after it is created?

    No. The current tools only allow for the creation of new tables. You cannot use the AI to alter existing ones.

  • 04

    Does the AI handle the actual data insertion?

    No. This specific task is for provisioning the table structure. You will need to handle the data ingestion separately.

  • 05

    Can I see what tables are already there?

    Yes. The AI can list all existing tables in your LanceDB instance so you can verify your setup.

  • More questions about LanceDB? See everything the LanceDB Connector can do

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