trigger_pipeline

Trigger a new pipeline.

Server GitLab MCP Server skmprb/gitlab-clone-mcp-server
Category Execute
Risk class High
Parameters 00 required

What trigger_pipeline does on GitLab MCP Server

AI agents invoke trigger_pipeline to trigger actions in GitLab MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

Why trigger_pipeline needs a policy

This tool executes external operations (CI/CD pipelines) whose side effects depend on pipeline configuration arguments. Pipelines typically run tests, build processes, and deployments. While not necessarily destructive on their own, triggering pipelines can have significant side effects including resource consumption, deployment changes, or test environment modifications. This is firmly in the Execute category.

From the tool's definition Tool name: 'trigger_pipeline'. Description: 'Trigger a new pipeline.' The verb 'trigger' combined with 'pipeline' indicates initiation of a CI/CD execution workflow whose effects depend on the pipeline configuration and may include running tests, deployments,…

Questions about trigger_pipeline

What does the trigger_pipeline tool do? +

Trigger a new pipeline. It is categorised as a Execute tool in the GitLab MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on trigger_pipeline? +

Register the GitLab MCP Server MCP server in PolicyLayer and add a rule for trigger_pipeline: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches GitLab MCP Server. Nothing to install.

What risk level is trigger_pipeline? +

trigger_pipeline is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit trigger_pipeline? +

Yes. Add a rate_limit block to the trigger_pipeline rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block trigger_pipeline completely? +

Set action: deny in the PolicyLayer policy for trigger_pipeline. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides trigger_pipeline? +

trigger_pipeline is provided by the GitLab MCP Server MCP server (skmprb/gitlab-clone-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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