How to Use the Woodpecker CI MCP in Google ADK

Q: How do I check the status of a deployment using Woodpecker CI and Google ADK?

You can use getpipeline to pull specific details about any running job. If you need to see everything for one project, run listpipelines. The agent handles parsing these results into actionable data.

Q: What's the protocol for restarting a failed build using Woodpecker CI and Google ADK?

Simply use the restartpipeline tool. This forces the job to run again from scratch, which is often required when debugging data flow errors in your connected systems.

Q: Can I see all the repositories available through Woodpecker CI and Google ADK?

Absolutely. The listrepos tool provides a full inventory of every repository on the server. You can use this list to feed into other actions, like updating settings or getting details.

Q: Does Woodpecker CI and Google ADK handle secret storage?

Yes. The system supports listing both global secrets (listglobalsecrets) and repository-specific credentials (listreposecrets). This central management keeps your sensitive data organized.

Q: What kind of data does this MCP Server touch regarding privacy?

This server manages sensitive repository settings and system user details. When the agent runs, it has access to information about which users own what resources and where those resources are configured.

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Connect Woodpecker CI MCP to Google ADK

Create your Vinkius account to connect Woodpecker 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 Woodpecker CI with Google ADK

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Perplexity

Initiate and repair complex build processes.

Need a data pipeline to run? Use `trigger_pipeline` to kick off a job. If the webhook breaks, no sweat; call `repair_repo` to fix it. The agent ensures that your CI process is always kicking off correctly.

Maintain full visibility of organizational structure.

The system lets you map out your entire company setup. You can list all organizations with `list_orgs`, and then focus down to specific teams using `list_agents` or `list_org_agents`. This gives a clear view of who owns what.

Manage user access and resource ownership.

Your agent controls permissions with calls like `get_org_permissions`. Ownership changes are straightforward: use `chown_repo` to reassign management rights. This is key for building reliable, enterprise-grade agents.

Setup guide

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

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Common questions about Woodpecker CI MCP in Google ADK

You can use `get_pipeline` to pull specific details about any running job. If you need to see everything for one project, run `list_pipelines`. The agent handles parsing these results into actionable data.

Simply use the `restart_pipeline` tool. This forces the job to run again from scratch, which is often required when debugging data flow errors in your connected systems.

Absolutely. The `list_repos` tool provides a full inventory of every repository on the server. You can use this list to feed into other actions, like updating settings or getting details.

Yes. The system supports listing both global secrets (`list_global_secrets`) and repository-specific credentials (`list_repo_secrets`). This central management keeps your sensitive data organized.

This server manages sensitive `repository settings` and system user details. When the agent runs, it has access to information about which users own what resources and where those resources are configured.

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