How to Use the Marqo AI (Vector Search & Embeddings) MCP in Cline

Q: What about data privacy when Cline connects to the Marqo AI (Vector Search & Embeddings) server?

Your code and the document data sent to adddocuments or deletedocuments are streamed directly to the MCP server for processing. Each Vinkius server runs in a zero-trust environment, so the instance handling your request is destroyed immediately after. Your data is never persisted.

Have Cline build complete features powered by Marqo AI, from writing the indexing script to generating the UI component that searches it.

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Connect Marqo AI (Vector Search & Embeddings) MCP to Cline

Create your Vinkius account to connect Marqo AI (Vector Search & Embeddings) to Cline and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Marqo AI (Vector Search & Embeddings) with Cline

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Generate Search Backends from a Prompt

Ask Cline to 'add semantic search for our articles.' It won't just give you code snippets. Cline writes the actual script that calls `create_index` and then uses `add_documents` to populate your new Marqo index. It understands the context of your project, so the generated code fits your existing patterns. You get a file that's ready to review and commit, not a block of text to copy-paste.

Build and Manage Indices with Cline

You don't need a separate tool to check on your Marqo setup. Just ask Cline, 'are there any Marqo indexes?' and it will run `list_indexes` and show you the results right in the chat. This makes debugging way faster. If a search is failing, you can ask your agent to `get_index_stats` for the index in question or even write a script to `delete_documents` that are causing problems.

A Full-Stack Search Feature via MCP Server

The real test is getting search into your app. Tell Cline: 'build a React component that uses `tensor_search` on the 'articles' index.' It will write the component, handle state, and fetch data from your Marqo instance. Cline generates the whole feature. It writes the API endpoint that executes the search and the frontend code that calls it. This MCP connection gives you a working feature, not just a function.

Setup guide

Set up Marqo AI (Vector Search & Embeddings) MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type marqo-ai-vector-search-embeddings-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest Marqo AI (Vector Search & Embeddings) refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

{
  "mcpServers": {
    "marqo-ai-vector-search-embeddings-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Marqo AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about Marqo AI (Vector Search & Embeddings) MCP in Cline

Cline writes production-ready code. For Marqo, that means Python scripts for `add_documents`, API route handlers in your framework for `tensor_search`, and even frontend components in React or Vue that call those routes.

Yes. After generating the code, you can ask Cline to 'write a test for this search component.' It will create a test file that mocks the `tensor_search` call and asserts that the component renders the results correctly.

Cline reads your open files and project structure. When you ask it to write an indexing script using the Marqo AI (Vector Search & Embeddings) tools, it matches your existing coding style, imports, and framework conventions.

Absolutely. You can provide Cline with a list of document IDs and instruct it to 'write a script to remove these documents.' It will generate the necessary code using the `delete_documents` tool from this MCP server.

Your code and the document data sent to `add_documents` or `delete_documents` are streamed directly to the MCP server for processing. Each Vinkius server runs in a zero-trust environment, so the instance handling your request is destroyed immediately after. Your data is never persisted.

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