How to Use the Dagger (Programmable CI) MCP in Google ADK

Connect your Google ADK agents to build pipelines. Use Dagger (Programmable CI) to manage cloud infrastructure tasks.

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Connect Dagger (Programmable CI) MCP to Google ADK

Create your Vinkius account to connect Dagger (Programmable CI) 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 Dagger (Programmable CI) with Google ADK

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Orchestrate Google ADK build environments

Create scratch containers using `query_container` to run your build steps. Your agent manages the lifecycle of these containers, ensuring they spin down once the job finishes. This setup works well with your existing cloud infrastructure. It keeps your build environment ephemeral and isolated from your primary development machine.

Direct Git and HTTP integration for Google ADK

Use `query_git` to fetch specific repositories for your build pipelines. Your agent handles the branch logic and pulls the exact source code required for the current task. `query_http` lets you pull external files or dependencies on demand. This avoids hardcoding paths, letting your agent grab what it needs during runtime.

Build module-aware agents in Google ADK

Use `query_current_module` to map your project directory. Your agent understands the local build structure, allowing it to navigate complex modules without human intervention. Combine this with `query_directory` to define workspace layouts dynamically. Your agent creates the required folder structure before executing the next GraphQL build step.

Setup guide

Set up Dagger (Programmable CI) 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 Dagger (Programmable CI) 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="Dagger (Programmable CI)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Dagger (Programmable CI) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Dagger (Programmable CI) MCP in Google ADK

You pass the server parameters to the McpToolset component. This registers all tools as native agent capabilities, allowing you to invoke them within your LLM agents.

Yes, the server supports both Stdio and HTTP transports. You choose the connection method that fits your local development environment or production deployment.

No, the toolset is modular. You can filter the tools exposed to your agent, ensuring only the relevant build operations are available during a specific workflow.

The agent can reason over the entire build log returned by the tools. This is useful for debugging complex failures that span thousands of lines of output.

The server operates on a per-request basis with ephemeral storage. It only accesses the build directory and secrets you explicitly provide during a task execution.

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