How to Use the Dagster MCP in Google ADK

Connect Gemini agents to your data pipelines with Google ADK and the Dagster MCP Server.

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Connect Dagster MCP to Google ADK

Create your Vinkius account to connect Dagster 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 Dagster with Google ADK

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Analyze Dagster Run Logs inside Google ADK

The `list_runs` and `get_run` tools fetch pipeline execution metadata directly into your Gemini agent via the MCP Server. This allows your agent to match failed pipeline runs with downstream tables in BigQuery. Gemini's million-token context window handles massive run logs without breaking a sweat. You feed the entire raw traceback from a failed run into the model to find the broken database query in seconds.

Map Software-Defined Assets to Vertex AI

The `list_assets` tool exposes your entire Dagster asset catalog to Google ADK. Your agent checks the asset graph to find out which machine learning models need retraining based on new data arrivals. Data engineering meets AI here. Our agent reads the asset status, verifies the upstream dependencies, and triggers Vertex AI training jobs only when the data is fresh.

Track Active Jobs, Schedules, and Sensors

The `list_jobs`, `list_schedules`, and `list_sensors` tools give your Google Cloud agent full visibility into pipeline timing. It queries these tools to see if a sensor missed an external file arrival. You get clean, structured data back from the server. Gemini uses this info to update your operational dashboards or ping your team on Google Chat when a schedule slips.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Dagster. 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.

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Common questions about Dagster MCP in Google ADK

Use the McpToolset class from the Google ADK library and point it to your Vinkius HTTP endpoint. Pass this toolset directly to your LlmAgent to expose the tools.

Absolutely. Pass the output of the run details tool directly into the agent's prompt, letting Gemini analyze thousands of lines of pipeline logs in one go.

Yes, the framework connects to the Vinkius hosted endpoint over streamable HTTP, but you can also run it locally via Stdio for debugging.

Pass a filtered list of tool names to your toolset parameters. This prevents the agent from seeing or executing tools like run detail fetching.

Yes, Vinkius handles all authentication via a single secure token. Your data flows through a zero-trust, ephemeral sandbox, so no pipeline metadata is stored on the host.

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