How to Use the Vertex AI Vector Search MCP in Cline

Q: How do I check my available indexes for Vertex AI Vector Search using Cline?

Run listvectorindexes to see all vector indexes in your project. This gives you the names needed for subsequent operations and searches.

Q: What input is required when running Vertex AI Vector Search with Cline?

The core search function, searchnearestneighbors, requires three pieces of information: an endpoint ID, a deployed index ID, and the query vector as a JSON array.

Q: If I'm debugging a Vector Search feature with Cline, what tools help?

Check listvectoroperations for long-running status updates. You can also use getindexdetails to validate the index configuration before attempting the search again.

Q: Does Vertex AI Vector Search support metadata checks with Cline?

Yes, you can call getindexdetails. This retrieves the full metadata and operational setup for any vector index in your cloud project.

Execute vector similarity searches inside VS Code with Cline’s autonomous agent.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Vertex AI Vector Search MCP to Cline

Create your Vinkius account to connect Vertex AI Vector Search 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.

GDPR Free for Subscribers

Setup Vertex AI Vector Search with Cline

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Perform nearest neighbor lookups.

The `search_nearest_neighbors` tool lets you execute complex vector similarity searches directly from your code flow. You provide the endpoint ID, deployed index ID, and a query vector array. Cline runs this operation end-to-end: it calls the necessary tools, processes the results, and presents the final data structure right in your editor.

List all available indexes.

Need to know what's deployed? Use `list_vector_indexes` to pull a complete inventory of every vector index in your Google Cloud project. This helps Cline scope out the right data source. If you need more context, running `list_index_endpoints` shows all available endpoints for those indexes.

Get detailed index configurations.

The `get_index_details` tool pulls specific metadata and configuration for a vector index. This is crucial when building reliable components. If your component requires specific settings, you can pull those details here before writing the search logic into your code.

Setup guide

Set up Vertex AI Vector Search 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 vertex-ai-vector-search-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 Vertex AI Vector Search 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": {
    "vertex-ai-vector-search-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 Vertex AI Vector Search. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Vertex AI Vector Search now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Vertex AI Vector Search MCP in Cline

Run `list_vector_indexes` to see all vector indexes in your project. This gives you the names needed for subsequent operations and searches.

The core search function, `search_nearest_neighbors`, requires three pieces of information: an endpoint ID, a deployed index ID, and the query vector as a JSON array.

Check `list_vector_operations` for long-running status updates. You can also use `get_index_details` to validate the index configuration before attempting the search again.

Yes, you can call `get_index_details`. This retrieves the full metadata and operational setup for any vector index in your cloud project.

This server handles Vector Index Metadata. It manages structural information, including configurations and endpoints, for the vector indexes you are querying.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript