Use Vertex AI Vector Search with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Bring Google's massive vector matching power to your AI agent. Search billions of semantic embeddings and administer Vertex Index endpoints directly in chat.
Developed, maintained, and hosted by Vinkius.
MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED
Waiting for input…
Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.
Complete set · 6 capabilities
The complete Vertex AI Vector Search capability set.
These are the exact actions your AI can choose when you ask it to work with Vertex AI Vector Search.
01-03
3 capabilities in this set.
Part of 6 available through Vertex AI Vector Search.
- 01
List deployed indexes
Lists all indexes deployed to a specific endpoint
- 02
List index endpoints
Lists all index endpoints in the project
- 03
List vector operations
Lists long-running operations related to vector indexes
04-06
3 capabilities in this set.
Part of 6 available through Vertex AI Vector Search.
- 04
Get index details
Retrieves metadata and configuration for a specific vector index
- 05
List vector indexes
Lists all vector indexes in the Google Cloud project
- 06
Search nearest neighbors
Provide the endpoint ID, deployed index ID, and a query vector as a JSON array. Performs a nearest neighbor vector similarity search
Observed, not estimated
846ms average. Fast in production.
Vertex AI Vector Search is checked daily against the live service.
- Fastest day
- 674ms
- Slowest day
- 1005ms
- 14-day trend
- Slowing+19%
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 Vertex AI Vector Search, so you can see the experience inside your AI.
It does not authenticate your account with Vertex AI Vector Search. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Vertex AI Vector Search Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_7qmxXVVjzgLzy5Qveg1Au3aDsjeacjAMcHp2XBIt/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Vertex AI Vector Search capabilities are ready to use.
{
"mcpServers": {
"vertex-ai-vector-search-mcp": {
"url": "https://edge.vinkius.com/vk_preview_7qmxXVVjzgLzy5Qveg1Au3aDsjeacjAMcHp2XBIt/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
FAQ
Questions Vertex AI Vector Search owners ask.
- 01
How do I perform a nearest-neighbor similarity test via chat?
Just write: Search my endpoint '1xxx' against index 'deployed_abc_1' looking for 3 nearest neighbors to the vector [0.015, -0.042, 0.111]. The queryIndexTool bridges to Vertex and returns the IDs and distances of your geometrical matches instantly.
- 02
Can I query a status for indices that take hours to build on GCP?
Absolutely. Use the prompt: Check my google cloud vector operations. The listOperationsTool reveals all in-flight Cloud operations indicating completion percentages and precise timestamps, allowing you to sidestep the Google Console completely.
- 03
Where do I easily find the short-lived VERTEX_ACCESS_TOKEN?
On your terminal with gcloud installed and logged in, simply type gcloud auth print-access-token. Copy the output stream starting with ya29... into your configurations and the integration is ready for connection.
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