How to Use the Workato MCP in Google ADK

Use Workato with Google ADK to act directly on your cloud data, monitoring recipes and connections via Gemini models.

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Connect Workato MCP to Google ADK

Create your Vinkius account to connect Workato 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 Workato with Google ADK

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Analyze Automation Jobs

Your agent can check the status of recent workflow runs by calling `list_recipe_jobs`. Since you're running this on Google Cloud, your 1M+ token context allows Gemini to correlate job failures with overall system health. You don't have to look at logs one by one. This deep analysis works alongside tools like `get_recipe_details`, helping the agent understand *why* a job failed based on its expected parameters.

Map Workato Resources

The Google ADK allows you to map your entire iPaaS environment. Use `list_workato_folders` to see how your team organizes work, and then use `get_api_collections` to find out what services are exposed in the platform's API layer. These structured outputs feed directly into Gemini for reasoning, allowing it to build a coherent picture of your infrastructure.

Inventory Connections & Recipes

Need an inventory? The agent pulls every configured app connection using `list_app_connections` and lists all current automation recipes via `list_automation_recipes`. This data is perfect for feeding into BigQuery for long-term auditing. It also helps you see what connectors are available in your tenant by calling `list_managed_connectors`.

Setup guide

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

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Common questions about Workato MCP in Google ADK

Your agent uses Gemini's long context to process the complex, varied data structures returned by the MCP Server. It treats every list (like `list_automation_recipes`) as a rich dataset ready for analysis in BigQuery.

Yes. The agent can pull details on specific workflows using `get_recipe_details` and track their recent activity with the `list_recipe_jobs` tool, all within your cloud environment.

The agent accesses structural information about your platform: app connections via `list_app_connections`, folder structures using `list_workato_folders`, and available API endpoints through `get_api_collections`.

It does. Because it supports 1M+ tokens, you can pass multiple lists—like all recipes and all connections—to Gemini for a single, comprehensive audit in Vertex AI.

The server touches application connection details. It provides metadata related to your configured app connections, which is essential for running security audits and understanding who has access across your cloud assets.

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