Google Vertex AI

Give Agent Designer agents access to your enterprise data context in DataHub — prototype data agents visually using the low-code builder in Vertex AI Agent Builder.

Note: Agent Designer is currently a preview feature.

Prerequisites

• A Google Cloud project with Vertex AI Agent Builder enabled
• A DataHub instance with the MCP server enabled

Setup

1. Open Agent Designer and click Create agent.
2. Set a name, instructions (e.g., "You are a data catalog assistant. Use DataHub tools to find datasets, schemas, and lineage."), and pick a model (e.g., Gemini 2.5 Flash).
3. Click Add tools → MCP Server.
4. Enter a display name (e.g., DataHub) and your MCP endpoint URL.
5. Click Save — Agent Designer discovers the tools automatically.
6. Use the Preview tab to test.

MCP Authentication Limitation

The Agent Designer UI only supports MCP servers that do not require authentication. If your DataHub instance requires a bearer token, use the Get code button to export the agent, then add the Authorization header manually:

from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams

toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://<tenant>.acryl.io/integrations/ai/mcp"
    ),
    headers={"Authorization": f"Bearer {YOUR_TOKEN}"},
)

See the Google ADK Integration for a complete working example.

Exporting to Code

Click Get code to export your agent as Python, then continue development with the Google ADK or LangChain. This lets you prototype visually and transition to code for production.

Links: Agent Designer Docs · Google ADK Integration · Agent Context Kit