How to Use the Woodpecker CI MCP in CrewAI

Q: Can CrewAI list all repositories using Woodpecker CI?

Yes. Using the listrepos tool, your specialized crew can immediately see every repository on file. This provides the foundational data needed for any operation.

Q: What if I need to repair a repo webhook using Woodpecker CI with CrewAI?

A designated maintenance agent runs repairrepo. It's a simple, direct action that fixes webhooks without needing human intervention or manual steps.

Q: Does Woodpecker CI support full user oversight with CrewAI?

Yes. The crew can list all users using listusers (admin only), and check the current user's details with getuser. This is critical for role-based operations.

Build autonomous teams: Running Woodpecker CI with CrewAI's agent framework.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Woodpecker CI MCP to CrewAI

Create your Vinkius account to connect Woodpecker CI to CrewAI 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 Woodpecker CI with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Autonomous repo management via MCP Server.

A specialized crew can handle all repository tasks. They can look up a project by name using `lookup_repo`, or even delete the entire setup with `delete_repo`. If you suspect webhook issues, a worker agent simply runs `repair_repo`. This capability means your autonomous operations never get stuck on broken infrastructure.

Monitoring and controlling pipelines using MCP Server.

The crew can monitor deployments by listing all active builds with `list_pipelines`. Need to intervene? A designated agent runs `cancel_pipeline` if the job is going sideways. They also manage restarts, triggering a new run via `restart_pipeline` when necessary. You get total control over your deployment cycle.

Handling users and agents with MCP Server.

The crew can maintain the workforce itself. They list all active workers using `list_agents`, or create a new specialist agent via `create_agent`. You can even update their role later using `update_agent`. For user oversight, an admin agent uses `get_user` to check who's logged in.

Setup guide

Set up Woodpecker CI MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Woodpecker CI tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Woodpecker CI Analyst",
    goal="Access and analyze Woodpecker CI data via MCP.",
    backstory="Expert analyst with direct Woodpecker CI access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Woodpecker CI transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Woodpecker CI Analyst",
        goal="Access and analyze Woodpecker CI data via MCP.",
        backstory="Expert analyst with direct Woodpecker CI access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Woodpecker CI transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 Woodpecker CI. 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 Woodpecker CI 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 Woodpecker CI MCP in CrewAI

The agents collaborate: one might research the necessary config using `get_pipeline_config`, and another might then trigger the build with `trigger_pipeline`. The process is fully automated.

Yes. Using the `list_repos` tool, your specialized crew can immediately see every repository on file. This provides the foundational data needed for any operation.

A designated maintenance agent runs `repair_repo`. It's a simple, direct action that fixes webhooks without needing human intervention or manual steps.

Yes. The crew can list all users using `list_users` (admin only), and check the current user's details with `get_user`. This is critical for role-based operations.

The server touches repository secrets. Your autonomous crew can list and manage these credentials using tools like `list_repo_secrets` and `create_repo_secret`, keeping your sensitive data secure.

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