How to Use the Vertex AI Vector Search MCP in Claude Code

Q: How do I list available indexes for Vertex AI Vector Search using Claude Code?

Run listvectorindexes from your terminal. This command pulls a comprehensive list of all vector indexes in the Google Cloud project, giving you the IDs needed to proceed.

Q: What parameters are required for Vertex AI Vector Search using Claude Code?

The searchnearestneighbors tool requires an endpoint ID, a deployed index ID, and your query vector as a JSON array. All three must be passed to the command.

Q: If my pipeline fails on Vertex AI Vector Search using Claude Code, how do I debug it?

Use listvectoroperations first. This shows long-running operations and status updates related to your vector indexes, pointing you toward the failure point.

Q: Can I validate index setup using Claude Code's MCP Server?

Yes, use getindexdetails. It retrieves the full metadata and configuration for a specific vector index. This is great for pre-flight checks in your automation scripts.

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Setup Vertex AI Vector Search with Claude Code

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Execute vector similarity search via script.

The `search_nearest_neighbors` tool lets you run a full vector similarity query from the command line. You must provide an endpoint ID, the deployed index ID, and your query vector as a JSON array. This is perfect for CI/CD: write a shell script that executes this search and pipes the resulting data into another build step.

List all project indexes for scripting.

Use `list_vector_indexes` to pull an inventory of every vector index in your Google Cloud project. This list provides the necessary IDs you'll need to hardcode into a pipeline script. Before searching, it’s smart practice to check this list to ensure the target index exists.

Inspect deployment endpoints.

The `list_index_endpoints` tool lists all active index endpoints for your project. If your script needs a specific endpoint ID, running this command guarantees you grab the correct, deployable version. This is essential for reliability when scripting automated searches.

Setup guide

Set up Vertex AI Vector Search MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see vertex-ai-vector-search-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest Vertex AI Vector Search transactions." It will automatically discover and invoke the available Vertex AI Vector Search tools.

Terminal

claude mcp add --transport http vertex-ai-vector-search-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the Vertex AI Vector Search MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "vertex-ai-vector-search-mcp": {
      "type": "url",
      "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.

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Common questions about Vertex AI Vector Search MCP in Claude Code

Run `list_vector_indexes` from your terminal. This command pulls a comprehensive list of all vector indexes in the Google Cloud project, giving you the IDs needed to proceed.

The `search_nearest_neighbors` tool requires an endpoint ID, a deployed index ID, and your query vector as a JSON array. All three must be passed to the command.

Use `list_vector_operations` first. This shows long-running operations and status updates related to your vector indexes, pointing you toward the failure point.

Yes, use `get_index_details`. It retrieves the full metadata and configuration for a specific vector index. This is great for pre-flight checks in your automation scripts.

This server handles Vector Index Metadata. It exposes the structure definitions, configurations, and operational details for the vector indexes managed by the project.

Use it with your favorite AI tools

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

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