How to Use the Airbyte MCP in Google ADK

Q: How do I set up the Airbyte MCP Server in Google ADK?

Run pip install google-adk to get the framework. Create an McpToolset using StreamableHttpServerParameters with your Vinkius URL, then pass it to your LlmAgent tools array.

Q: Can Google ADK restrict which Airbyte tools the agent uses?

The McpToolset accepts a toolnames array during setup. Passing just 'listjobs', 'getconnection' prevents the agent from calling anything else.

Feed Airbyte pipeline metadata into your Google ADK agents to monitor syncs across BigQuery and Vertex AI.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Airbyte MCP to Google ADK

Create your Vinkius account to connect Airbyte 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 Airbyte with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Analyze Sync Jobs with Google ADK

Calling `list_jobs` pulls the complete execution history for a specific connection. Your Gemini agent reads these logs to identify exactly when a synchronization task failed or stalled. It spots the exact timestamp things went wrong. Long-context reasoning allows the model to ingest thousands of job runs at once. It scans the historical data to find patterns in API timeouts or database locks affecting your transfers.

Read Workspace Topology

The `list_workspaces` tool gives your agent a top-level view of your data environments. From there, it executes `list_connections` to trace how records move from external APIs into your data warehouse. You get a clear map of your incoming data. Managing enterprise architecture requires knowing exactly what feeds your BigQuery tables. This MCP Server exposes the raw topology so your Google Cloud agents can map dependencies automatically.

Filter Airbyte Destinations

Retrieving destination configurations happens through the `list_destinations` tool. The agent checks if your current pipelines are pointing to the correct cloud storage buckets or analytical databases. It verifies your routing logic. You can restrict which tools the agent accesses using the `tool_names` filter in the `McpToolset` setup. This keeps the agent focused strictly on destination checks rather than source modifications.

Setup guide

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

Run `pip install google-adk` to get the framework. Create an `McpToolset` using `StreamableHttpServerParameters` with your Vinkius URL, then pass it to your `LlmAgent` tools array.

The `McpToolset` accepts a `tool_names` array during setup. Passing just `['list_jobs', 'get_connection']` prevents the agent from calling anything else.

Large workspace topologies return massive JSON payloads. Gemini processes these easily, allowing your agent to analyze hundreds of connections in a single prompt.

The framework supports HTTP and Stdio transports. Vinkius provides a managed HTTP endpoint, so you will use `StreamableHttpServerParameters` for the connection.

This integration reads workspace IDs, job logs, and destination schemas. The Vinkius zero-trust architecture requires a single endpoint token, ensuring no long-lived credentials leak while analyzing your pipeline metadata.

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