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Connect Lancedb Serverless Vector Db to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Manage your RAG infrastructure through natural conversation.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 6 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through LanceDB.

  1. 01

    Get table

    Retrieves the specific schema and metadata for a chosen LanceDB table.

  2. 02

    List tables

    Shows all the vectorized tables currently stored in your LanceDB instance.

  3. 03

    Create table

    Sets up a new LanceDB table using a strict, predefined schema.

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through LanceDB.

  1. 04

    Delete table

    Permanently removes an entire LanceDB vector table from your storage.

  2. 05

    Insert rows

    Adds new structured data and vectors to a table while updating the ANN index.

  3. 06

    Vector search

    Runs an optimized KNN similarity search to find related vectors.

Real work

What teams actually run

01

RAG Debugging

Check why a specific document isn't being retrieved by inspecting table schemas and search results.

02

Real-time Data Updates

Add new embeddings to your database and immediately use them in searches.

03

Schema Management

Provision new tables for multi-modal workloads using specific dimensional layouts.

04

Storage Cleanup

Remove old or unused vector tables to keep your serverless environment optimized.

Automate a task

Put LanceDB to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

LanceDB works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put LanceDB to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

922ms average. Fast in production.

LanceDB is checked daily against the live service.

Daily averagePeak 1081ms
Oct 3Today
Fastest day
762ms
Slowest day
1081ms
14-day trend
Slowing+6%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of LanceDB, so you can see the experience inside your AI.

It does not authenticate your account with LanceDB. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

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

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up LanceDB in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work LanceDB owners hand off.

This MCP is built for engineers who need to bridge the gap between vector data and AI reasoning.

  • 01

    RAG Developers

    They use the agent to verify document retrieval results without writing manual scripts.

  • 02

    Data Engineers

    They manage vector tables and strict schemas for multi-modal applications.

  • 03

    AI Architects

    They monitor vector topologies and audit storage across multiple instances.

FAQ

Questions LanceDB owners ask.

  • 01

    How do I connect my LanceDB account?

    You just need to provide your LanceDB API URL, API Key, and the specific Database Name when you subscribe to the MCP on Vinkius.

  • 02

    Which AI clients can I use with this MCP?

    You can use any MCP-compatible client, including Claude, Cursor, and Windsurf.

  • 03

    Does inserting data update the search index?

    Yes, when you use the insert_rows capability, the underlying ANN index updates in real-time.

  • 04

    Can I manage schemas through the AI?

    Yes, you can provision new tables with strict Apache Arrow schemas directly through your agent.

  • 05

    Is deleting a table reversible?

    No, the delete_table capability irreversibly removes the entire vector table.

  • 06

    Can I perform a semantic similarity search using my agent?

    Yes. Use the vector_search capability by providing the target Table name and a JSON array of floating-point numbers representing your query embedding. Your agent will return the k-nearest rows from LanceDB based on semantic similarity.

  • 07

    How do I create a new table with a specific Apache Arrow schema?

    The create_table capability allows your agent to initialize a new columnar vector table. You just need to provide the desired Table name and a valid Apache Arrow schema mapping in JSON format defining dimensions and scalar fields.

  • 08

    Can my agent insert new embeddings directly into a LanceDB table?

    Absolutely. Use the insert_rows capability to persist new data rows containing native embeddings and arbitrary JSON metadata. Your agent will handle the payload delivery, and LanceDB will automatically update its ANN index.

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