How to Use the Conduit MCP in Google ADK

Q: Does Conduit work with Google ADK tool filtering?

Yes, you can use the toolnames filter to restrict which operations your agent can perform. This is useful for limiting access to sensitive trigger tools.

Q: Can my Google ADK agent query active Conduit connections?

You simply call listconnections to get the current list. This allows the agent to verify that the sources and destinations are active.

Connect Conduit to Google ADK to let your Gemini agents act on live data integration pipelines.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Conduit MCP to Google ADK

Create your Vinkius account to connect Conduit 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 Conduit with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Control data pipelines from Google ADK

Use `trigger_workflow` to start your integration jobs right from your Gemini agent. It lets your infrastructure respond to events detected in your BigQuery environment. This tool allows the agent to push data when its long-context reasoning identifies a need. It bridges the gap between your cloud analytics and your data movement.

Query workflow states with Google ADK

Call `get_run_status` to see exactly what is happening inside your pipelines. Your agent parses these status updates to make informed decisions about downstream cloud tasks. It removes the need for manual checks in the platform UI. The agent now sees the real-time health of your data moving through the system.

Map your infrastructure using Google ADK

Invoke `list_available_sources` and `list_available_destinations` to understand your current setup. Your agent can then adjust pipelines based on the available connectors. This gives your code a map of the environment it operates within. It stops the agent from guessing which pipelines exist or where they lead.

Setup guide

Set up Conduit 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 Conduit 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="Conduit_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Conduit 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 Conduit. 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 Conduit 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 Conduit MCP in Google ADK

You use the McpToolset with your server URL and pass it to your LlmAgent. It integrates cleanly into your existing Google Cloud Python setup.

Yes, you can use the tool_names filter to restrict which operations your agent can perform. This is useful for limiting access to sensitive trigger tools.

You simply call `list_connections` to get the current list. This allows the agent to verify that the sources and destinations are active.

It shares only the metadata required for workflow management. This includes pipeline IDs, connection types, and execution status timestamps.

Every request is ephemeral and authenticated via your endpoint token. We never persist your workflow metadata beyond the active agent session.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python