• SCHEMA
  • DEPLOY
  • AUDIT
  • HUMAN

How to create vector search collections with your AI

Connect Typesense to your AI client once. From then on, your agent handles the schema design and deployment for your semantic search needs.

Ask AI about this page

Short answer

Can my AI build Typesense vector collections?

Yes. Your AI uses the connector to define new semantic search schemas and deploy them as collections. You'll get organized vector data ready for similarity searches.

The outcomes.

What your AI accomplishes.

The AI handles the heavy lifting of database configuration.

SCHEMA

Automated schema design

The AI interprets your natural language requirements to build the correct field types and vector configurations.

DEPLOY

Instant collection creation

Once the schema is ready, the AI pushes the configuration to Typesense to spin up the new collection.

AUDIT

Existing collection review

Your agent can look through your current vector setup to ensure new collections match your existing architecture.

HUMAN

Manual data oversight

You decide when a schema is perfect before the AI executes the deployment to your database.

The workflow

What your AI does when you request a new collection.

The AI acts as a bridge between your intent and the Typesense API.

  1. Analyze requirements

    Your agent parses your description of the data you want to search to determine necessary fields and vector dimensions.

    list_vector_collections

  2. Check existing setup

    The AI looks at what you already have in Typesense to prevent naming conflicts or redundant structures.

    list_vector_collections

  3. Build the schema

    The AI translates your plain English instructions into a valid JSON configuration for the database.

    create_collection

  4. Deploy collection

    The AI sends the final configuration to Typesense to create the live vector collection.

    create_collection

Try it

Copy these to start.

Use these prompts to kick off the process with your agent.

Starting points

These are starting points. Swap out the bracketed text with your specific field names and vector dimensions.

Typesense Vector Search Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_bmlNohSGzzJmxN6goNUndx2uYrEvS88xXUYpe92K/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 — Typesense Vector Search capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "typesense-vector-search-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_bmlNohSGzzJmxN6goNUndx2uYrEvS88xXUYpe92K/mcp"
    }
  }
}
Copy into chat04

  • Create a new Typesense collection for my product catalog with vector support for descriptions.

  • List all my current vector collections so we can see what's already active.

  • Set up a semantic search collection for a library of PDF documents with 1536 dimensions.

  • Check my existing vector collections and suggest a new one for user profile embeddings.

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

Start here

Connect Typesense Vector Search once, then ask.

Just follow the link to connect your account. Your credentials stay encrypted, and you can start managing collections through your AI immediately.

Connect Typesense Vector Search to your AI

FAQ

How the task behaves

  • 01

    Can the AI delete my existing collections?

    No. The current tools only allow for listing and creating collections. Deletion remains a manual task for you.

  • 02

    Does the AI choose the vector dimensions for me?

    The AI will suggest dimensions based on your description, but you should always confirm the specific vector size before deployment.

  • 03

    Can I use this to upload actual data records?

    No. This specific set of tools is for managing the collection schemas and structure, not for ingesting individual documents.

  • 04

    Will the AI overwrite my current collections?

    No. The AI can only create new collections. It does not have the capability to modify or overwrite existing ones.

  • 05

    How does the AI know which fields to make searchable?

    The AI uses your natural language instructions to decide which fields require vector embeddings and which should be standard searchable attributes.

  • More questions about Typesense Vector Search? The Connector page answers them. See everything the Typesense Vector Search Connector can do

Connect Typesense Vector Search to Claude, Cursor, ChatGPT & more