Retry failed jobs in pipeline.
AI agents invoke gitlab_retry_pipeline to trigger actions in 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 failed pipeline jobs triggers re-execution of CI/CD jobs. This is an Execute action as it runs jobs/code again. It doesn't delete data, move money, or simply read/write data — it causes external operations (job execution) to run again. Misuse could waste compute resources or re-trigger side effects of those jobs, hence medium severity.
From the tool's definition Retry failed jobs in pipeline
Documented attack patterns abuse exactly the kind of access gitlab_retry_pipeline gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Gitlab, and nothing reaches the server without passing your rules. This is the rule we recommend for gitlab_retry_pipeline:
{
"version": "1",
"default": "deny",
"tools": {
"gitlab_retry_pipeline": {
"limits": [
{
"counter": "gitlab_retry_pipeline_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}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.
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Retry failed jobs in pipeline. It is categorised as a Execute tool in the Gitlab MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Gitlab 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 Gitlab. 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 Gitlab MCP server (mcpland/gitlab-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Gitlab, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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190 Gitlab tools catalogued and risk-classified — across an index of 43,000+ MCP servers.