This record as markdown: /tools/sagemcp-sagemcp/gitlab-retry-pipeline.md
What gitlab_retry_pipeline does on Sage MCP
AI agents invoke gitlab_retry_pipeline to trigger actions in Sage MCP. 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 gitlab_retry_pipeline is rated High
This tool re-triggers pipeline execution (CI/CD jobs) in GitLab. Retrying failed jobs causes external code execution, deployment scripts, and automated processes to run again. The blast radius is high because an AI agent could repeatedly trigger pipeline runs, causing unintended deployments, resource consumption, or side effects from re-running jobs in production environments.
From the tool's definition Retry all failed jobs in a pipeline
Attacks that exploit this kind of access
The rule that runs gitlab_retry_pipeline safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Sage MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For gitlab_retry_pipeline, this is the rule to start with:
gitlab_retry_pipeline stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Sage MCP, apply this rule, and every gitlab_retry_pipeline call is checked against it from then on.
Questions about gitlab_retry_pipeline
Retry all failed jobs in a pipeline. It is categorised as a Execute tool in the Sage MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Sage MCP server in PolicyLayer and add a rule for gitlab_retry_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 Sage MCP. Nothing to install.
gitlab_retry_pipeline is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the gitlab_retry_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.
Set action: deny in the PolicyLayer policy for gitlab_retry_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.
gitlab_retry_pipeline is provided by the Sage MCP server (sagemcp/sagemcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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