How to Use the Activepieces MCP in Google ADK

Q: How does Activepieces integrate with Google Cloud data?

Your Gemini agent can read execution logs using getflowrun and push that data directly to BigQuery. This allows you to build real-time monitoring dashboards on Google Cloud.

Run enterprise-scale Activepieces automations directly from your Gemini models using the Google ADK framework.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Activepieces MCP to Google ADK

Create your Vinkius account to connect Activepieces 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.

GDPR Free for Subscribers

Setup Activepieces with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Enterprise Workspace Control

`list_projects` lets your Gemini agent map out your entire enterprise workspace structure across multiple departments using this MCP Server. The agent uses `create_project` to spin up isolated environments for new teams on demand. Because Gemini handles massive token contexts, it can ingest your entire flow catalog at once. This makes it easy for your agent to coordinate complex cross-project tasks without losing track of the big picture.

Google ADK Git Sync and Deployments

`configure_git_repo` links your Activepieces projects to your enterprise Git repositories for version control. Your Gemini agent can programmatically commit changes or pull updates using this tool. When your team is ready to push to production, the agent calls `create_project_release` to deploy the latest version. This keeps your CI/CD pipeline clean and fully automated.

Deep Execution Analysis

`list_records` pulls internal data tables directly into your Google ADK agent for processing. You can combine this data with BigQuery datasets to run deep analytical queries on your business operations. If the agent finds discrepancies, it updates the specific rows using `update_record` to keep your systems in sync. This bridges the gap between your raw databases and active workflows.

Setup guide

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

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 Activepieces. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Activepieces now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Activepieces MCP in Google ADK

Install the package and initialize the toolset using your Vinkius HTTP endpoint. Pass the toolset directly into your agent configuration to expose the Activepieces automation tools to Gemini over this MCP connection.

Yes, you can use the optional tool name filter when initializing your toolset. This lets you block destructive actions like `delete_project_member` while keeping read-only tools active via the MCP Server.

Your Gemini agent can read execution logs using `get_flow_run` and push that data directly to BigQuery. This allows you to build real-time monitoring dashboards on Google Cloud.

Gemini's million-token context window easily handles large payloads from `get_flow`. The agent can analyze complex, multi-step automations in a single pass without running out of memory.

Your workflow structures and execution logs are processed entirely within your secure Google Cloud VPC and the Vinkius zero-trust MCP sandbox. No credentials or raw payloads are ever exposed to public networks.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript