Retry a specific failed CI/CD job.
AI agents invoke retry_job_tool to trigger actions in MCP Gitlab. 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.
Retrying a CI/CD job triggers execution of pipeline jobs again, which runs code and external operations. This is an Execute-category action as it re-runs build/test/deploy scripts. Severity is medium because misuse could cause unintended deployments or resource consumption, but effects are generally reversible and scoped to the CI/CD system.
From the tool's definition Retry a specific failed CI/CD job
Attacks that exploit this kind of access
Retry a specific failed CI/CD job. It is categorised as a Execute tool in the MCP Gitlab MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP Gitlab MCP server in PolicyLayer and add a rule for retry_job_tool: 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 MCP Gitlab. Nothing to install.
retry_job_tool 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 retry_job_tool 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 retry_job_tool. 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.
retry_job_tool is provided by the MCP Gitlab MCP server (mcp-gitlab-crunchtools). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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