How to Use the Xata (Serverless DB) MCP in Google ADK

Q: How does Xata (Serverless DB) help with project resource monitoring for Google ADK?

You get a clear picture of capacity by running getprojectlimits. This tells the agent exactly what resources are left in the current project. It's essential for planning big data operations.

Q: Can I list all available organizations with Xata (Serverless DB) and Google ADK?

Absolutely, call listorganizations. This gives your agent a full inventory of every organizational container. It's the starting point for any multi-tenant application built on this MCP Server.

Q: What tools are available for Xata (Serverless DB) and Google ADK to manage credentials?

The agent can getbranchcredentials to read current keys. If those keys expire, it uses rotatebranchcredentials immediately. This keeps your data access always secure.

Q: What is the best way to handle multiple database updates using Xata (Serverless DB) and Google ADK?

Use executesqlbatch. Instead of running several separate queries, this method groups them into one transaction. It makes your agent's code cleaner and the data changes more reliable.

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Setup Xata (Serverless DB) with Google ADK

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Run Queries with Xata (Serverless DB) via Google ADK

The `execute_sql` tool lets your agent run specific SQL commands against any branch. It's direct: you pass the query, and the MCP Server runs it for you. This is perfect when your Gemini model needs to act on live data. Need to update a bunch of records? Use `execute_sql_batch`. This groups multiple statements together in one call. Your agent can trust that these operations happen as a single unit.

Build and Structure Data Models (Google ADK)

Your agent needs to know where the data lives first. It uses `list_projects` to see all available work areas within an organization. Then, it can scope down further by using `get_project` or `list_branches`. When a new area is needed, the agent calls `create_branch`. This ensures that your enterprise workflow always operates in a contained, isolated environment.

Manage User Access and Ownership (Google ADK)

Control who can access what. The MCP Server gives tools like `list_organizations` to scope the view. Your agent uses `send_invitation` when someone joins, or it calls `remove_member` if they leave. It also helps maintain ownership by letting your agent `update_organization` details or calling `get_branch_metrics` to monitor usage.

Setup guide

Set up Xata (Serverless DB) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Xata (Serverless DB) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Xata (Serverless DB)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Xata (Serverless DB) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Xata (Serverless DB) MCP in Google ADK

You get a clear picture of capacity by running `get_project_limits`. This tells the agent exactly what resources are left in the current project. It's essential for planning big data operations.

Absolutely, call `list_organizations`. This gives your agent a full inventory of every organizational container. It's the starting point for any multi-tenant application built on this MCP Server.

The agent can `get_branch_credentials` to read current keys. If those keys expire, it uses `rotate_branch_credentials` immediately. This keeps your data access always secure.

Use `execute_sql_batch`. Instead of running several separate queries, this method groups them into one transaction. It makes your agent's code cleaner and the data changes more reliable.

The server handles organizational membership details and project resource limits. Specifically, it manages `list_members` and `get_project_limits`, which are critical operational records.

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