How to Use the Vertex AI Search MCP in VS Code Copilot

Q: How do I use Vertex AI Search in VS Code Copilot?

You configure the MCP Server via .vscode/mcp.json and switch Copilot Chat to Agent mode. The agent then uses tools like searchdocuments to run queries against your data.

Q: Can VS Code Copilot list all my search engines with Vertex AI Search?

Yes, running listsearchengines provides a clear view of every configured engine in the collection. This is great for team-wide audits before deploying new code.

Q: Is this setup suitable for team-wide deployment with Vertex AI Search in VS Code Copilot?

Yes, because you commit the configuration to .vscode/mcp.json, every developer on the team automatically gets access to the same MCP Server tools.

Standardize team tools across VS Code Copilot. Your MCP Server connects everyone to corporate knowledge.

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Connect Vertex AI Search MCP to VS Code Copilot

Create your Vinkius account to connect Vertex AI Search to VS Code Copilot 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 Vertex AI Search with VS Code Copilot

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Search and ground answers with the MCP Server.

The `get_grounded_answer` tool lets every developer pull an answer grounded in your private data store. By committing the required configuration to `.vscode/mcp.json`, you ensure everyone uses the same source of truth. This guarantees that all code relying on internal knowledge is consistent across the whole team.

List and manage data sources via MCP Server.

Use `list_data_stores` to show your developers exactly what data collections exist. You can then use this output to drive code that initializes or validates connectivity, eliminating manual setup steps. It’s a reliable way to audit the scope of available knowledge sources.

Fetch user insights using MCP Server.

`get_recommendations` needs data store IDs and user event JSON. Copilot Chat can integrate this into team functions, creating code that processes personalized data streams. This means your entire engineering team has access to context-aware logic.

Setup guide

Set up Vertex AI Search MCP in VS Code Copilot

Prerequisites

VS Code 1.99 or later with GitHub Copilot extension
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and run "MCP: Add Server". Select HTTP (Streamable) as the server type. VS Code will create .vscode/mcp.json in your workspace.
2

Add the Vertex AI Search MCP

Paste the JSON snippet shown on the right into your .vscode/mcp.json. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Switch to Agent mode

Open Copilot Chat (Cmd+Shift+I / Ctrl+Shift+I) and switch to Agent mode using the dropdown. MCP tools are only available in Agent mode — they do not appear in Edit or Ask modes.
4

Verify the connection

In the Copilot Chat input, type # to list available tools. You should see the Vertex AI Search tools listed. Try asking: "List my recent Vertex AI Search transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "vertex-ai-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 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 Search MCP in VS Code Copilot

You configure the MCP Server via `.vscode/mcp.json` and switch Copilot Chat to Agent mode. The agent then uses tools like `search_documents` to run queries against your data.

Yes, running `list_search_engines` provides a clear view of every configured engine in the collection. This is great for team-wide audits before deploying new code.

It handles searching across documents and generating natural language answers grounded in your enterprise knowledge. The MCP Server makes that search context available to the chat agent.

Yes, because you commit the configuration to `.vscode/mcp.json`, every developer on the team automatically gets access to the same MCP Server tools.

This server interacts with indexed document content and user event data, allowing your team's code to process sensitive records while maintaining SOC 2 compliance.

Use it with your favorite AI tools

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