Woodpecker CI MCP Server for Pydantic AIGive Pydantic AI instant access to 34 tools to Activate Repo, Cancel Pipeline, Chown Repo, and more

Name: Woodpecker CI
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Woodpecker CI through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Woodpecker CI MCP Server for Pydantic AI is a standout in the Ship It category — giving your AI agent 34 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Woodpecker CI "
            "(34 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Woodpecker CI?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Woodpecker CI MCP Server

Connect your Woodpecker CI server to any AI agent to automate your continuous integration and deployment workflows through natural language.

Pydantic AI validates every Woodpecker CI tool response against typed schemas, catching data inconsistencies at build time. Connect 34 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Pipeline Control — List, trigger, restart, or cancel pipelines for any repository to keep your builds moving.
Agent Monitoring — View all connected agents, check their health metrics, and manage task assignments in real-time.
Repository Management — Activate new repositories, update settings, and repair webhooks without leaving your chat interface.
Secret & Config Management — Securely handle global, organization, or repository-level secrets and inspect pipeline configurations.
System Insights — Retrieve server version, health status, and performance metrics to ensure your CI infrastructure is running smoothly.

The Woodpecker CI MCP Server exposes 34 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 34 Woodpecker CI tools available for Pydantic AI

When Pydantic AI connects to Woodpecker CI through Vinkius, your AI agent gets direct access to every tool listed below — spanning ci-cd, pipelines, automation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

activate

Activate repo on Woodpecker CI

Activate a repository

cancel

Cancel pipeline on Woodpecker CI

Cancel a running pipeline

chown

Chown repo on Woodpecker CI

Change repository owner to the current user

create

Create agent on Woodpecker CI

Create a new Woodpecker agent

create

Create global secret on Woodpecker CI

Create a global secret

create

Create repo secret on Woodpecker CI

Create a repository secret

delete

Delete agent on Woodpecker CI

Delete an agent

delete

Delete pipeline on Woodpecker CI

Delete a pipeline

delete

Delete repo on Woodpecker CI

Deactivate/delete a repository

get

Get agent on Woodpecker CI

Get details of a specific agent

get

Get healthz on Woodpecker CI

Server health check

get

Get metrics on Woodpecker CI

Prometheus metrics (requires WOODPECKER_PROMETHEUS_AUTH_TOKEN if configured)

get

Get org permissions on Woodpecker CI

Get user permissions for an organization

get

Get pipeline on Woodpecker CI

Get details of a specific pipeline

get

Get pipeline config on Woodpecker CI

Get the configuration files used for a pipeline

get

Get repo on Woodpecker CI

Get repository details

get

Get user on Woodpecker CI

Get the currently authenticated user

get

Get version on Woodpecker CI

Get server version information

list

List agent tasks on Woodpecker CI

List tasks currently assigned to an agent

list

List agents on Woodpecker CI

List all Woodpecker agents

list

List global secrets on Woodpecker CI

List global secrets (Admin only)

list

List org agents on Woodpecker CI

List agents scoped to an organization

list

List org secrets on Woodpecker CI

List organization-level secrets

list

List orgs on Woodpecker CI

List all organizations

list

List pipelines on Woodpecker CI

List pipelines for a repository

list

List repo secrets on Woodpecker CI

List repository-level secrets

list

List repos on Woodpecker CI

List all repositories on the server

list

List users on Woodpecker CI

List all users (Admin only)

lookup

Lookup repo on Woodpecker CI

Lookup a repository by its full name (slug)

repair

Repair repo on Woodpecker CI

Repair repository webhooks

restart

Restart pipeline on Woodpecker CI

Restart a pipeline

trigger

Trigger pipeline on Woodpecker CI

Trigger a manual pipeline

update

Update agent on Woodpecker CI

Update an existing agent

update

Update repo on Woodpecker CI

Update repository settings

Connect Woodpecker CI to Pydantic AI via MCP

Follow these steps to wire Woodpecker CI into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 34 tools from Woodpecker CI with type-safe schemas

Why Use Pydantic AI with the Woodpecker CI MCP Server

Pydantic AI provides unique advantages when paired with Woodpecker CI through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Woodpecker CI integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Woodpecker CI connection logic from agent behavior for testable, maintainable code

Woodpecker CI + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Woodpecker CI MCP Server delivers measurable value.

Type-safe data pipelines: query Woodpecker CI with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Woodpecker CI tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Woodpecker CI and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Woodpecker CI responses and write comprehensive agent tests

Example Prompts for Woodpecker CI in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Woodpecker CI immediately.

"List all Woodpecker agents and show their current status."

"Find the repository 'vinkius/mcp-server' and trigger a new pipeline."

"Show me the last 5 pipelines for repository ID 42."

Troubleshooting Woodpecker CI MCP Server with Pydantic AI

Common issues when connecting Woodpecker CI to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Woodpecker CI + Pydantic AI FAQ

Common questions about integrating Woodpecker CI MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Woodpecker CI MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.