Compatible with every major AI agent and IDE
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 Vercel AI SDK?
The Vercel AI SDK gives every Woodpecker CI tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 34 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
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Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Woodpecker CI integration everywhere
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Built-in streaming UI primitives let you display Woodpecker CI tool results progressively in React, Svelte, or Vue components
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Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Woodpecker CI in Vercel AI SDK
Woodpecker CI and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Woodpecker CI to Vercel AI SDK 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 Vercel AI SDK
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 Vercel AI SDK 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 Vercel AI SDK
Every tool call from Vercel AI SDK 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 the Vercel AI SDK connect to MCP servers?
Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
Can I use MCP tools in Edge Functions?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp
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