Bring Ci Cd
to CrewAI
Learn how to connect Woodpecker CI to CrewAI 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 CrewAI?
When paired with CrewAI, Woodpecker CI becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Woodpecker CI tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Woodpecker CI in CrewAI
Woodpecker CI and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Woodpecker CI to CrewAI 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 CrewAI
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 CrewAI 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 CrewAI
Every tool call from CrewAI 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 CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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