Bring Ci Cd
to Pydantic AI
Learn how to connect Woodpecker CI to Pydantic AI and start using 34 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Woodpecker CI MCP Server?
Connect your Woodpecker CI server to any AI agent to automate your continuous integration and deployment workflows through natural language.
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.
How it works
- Subscribe to this server
- Provide your Woodpecker Server URL and Personal Access Token
- Start orchestrating your DevOps workflows from Claude, Cursor, or any MCP-compatible client
Who is this for?
- DevOps Engineers — Monitor build agents and troubleshoot failing pipelines using simple queries.
- Software Developers — Trigger builds and check pipeline status directly from the code editor.
- SREs & System Admins — Keep an eye on CI infrastructure health and manage secrets across the organization.
Built-in capabilities (34)
Activate a repository
Cancel a running pipeline
Change repository owner to the current user
Create a new Woodpecker agent
Create a global secret
Create a repository secret
Delete an agent
Delete a pipeline
Deactivate/delete a repository
Get details of a specific agent
Server health check
Prometheus metrics (requires WOODPECKER_PROMETHEUS_AUTH_TOKEN if configured)
Get user permissions for an organization
Get details of a specific pipeline
Get the configuration files used for a pipeline
Get repository details
Get the currently authenticated user
Get server version information
List tasks currently assigned to an agent
List all Woodpecker agents
List global secrets (Admin only)
List agents scoped to an organization
List organization-level secrets
List all organizations
List pipelines for a repository
List repository-level secrets
List all repositories on the server
List all users (Admin only)
Lookup a repository by its full name (slug)
Repair repository webhooks
Restart a pipeline
Trigger a manual pipeline
Update an existing agent
Update repository settings
Why Pydantic AI?
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.
- —
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
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Dependency injection system cleanly separates your Woodpecker CI connection logic from agent behavior for testable, maintainable code
Woodpecker CI in Pydantic AI
Woodpecker CI and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Woodpecker CI to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Woodpecker CI in Pydantic AI
The Woodpecker CI 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. All 34 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Woodpecker CI for Pydantic AI
Every tool call from Pydantic AI to the Woodpecker CI MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I trigger a new pipeline build for a specific repository?
Yes. Use the trigger_pipeline tool by providing the repository ID. You can also specify a branch or commit if needed to start a new execution immediately.
How do I check if my build agents are online and healthy?
You can use list_agents to see all connected agents and their status. For more detail on a specific agent, use get_agent or list_agent_tasks to see what it's currently working on.
Is it possible to manage environment secrets through this agent?
Yes, the server includes tools like create_repo_secret and list_repo_secrets to manage sensitive variables at the repository level, as well as global and organization-level secret tools.
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.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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