How to Use the Wolai MCP in Google ADK

Q: Can I query Wolai databases using the Google ADK?

Yes. The querydatabase tool is available for querying any connected Wolai database. This means your agents can pull specific, structured information directly from your data sources.

Q: Does the Google ADK support listing all Wolai pages?

It does. You simply call listpages via the MCP Server toolset. This gives you a complete inventory of every page in your Wolai workspace, which is critical for auditing.

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Connect Wolai MCP to Google ADK

Create your Vinkius account to connect Wolai to Google ADK 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 Wolai with Google ADK

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MCP Server: Structured Data Management in Wolai

Need to manage structured data? The agent first checks available fields using `get_database` before writing. You can list all databases with `list_databases`, then use `query_database` to pull specific records, or add new information via `create_database_row`. This keeps your enterprise data clean.

MCP Server: Creating and Updating Wolai Content

Your agent handles the full lifecycle of content. To start fresh, it calls `create_page` or generates new documents using `create_database_row`. It can retrieve existing details with `get_page`, ensuring you always work on the right version.

MCP Server: Comprehensive Wolai Discovery Tools

The agent doesn't just write; it finds. You can use `list_pages` to map out your entire site structure, or call `get_workspace_info` for general account details. It also uses `list_users` to keep track of who is collaborating in Wolai.

Setup guide

Set up Wolai 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 Wolai 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="Wolai_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Wolai tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Wolai MCP in Google ADK

You set up the MCP toolset and pass it to your LlmAgent. The framework handles the connection details, allowing you to build robust agents that act on Wolai data within the Gemini ecosystem.

The server touches page content, user profiles, database rows, and workspace metadata. Since you're building enterprise agents on GCP, this integration lets your agent act across multiple core business domains.

Yes. The `query_database` tool is available for querying any connected Wolai database. This means your agents can pull specific, structured information directly from your data sources.

It does. You simply call `list_pages` via the MCP Server toolset. This gives you a complete inventory of every page in your Wolai workspace, which is critical for auditing.

The integration provides native compatibility with BigQuery and Vertex AI. This means you can run complex reasoning on Wolai data that already lives in your secured Google Cloud infrastructure.

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