retry_pipeline

Retry a failed or canceled pipeline

SERVERGitlab Mcp SOURCE@zereight/mcp-gitlab

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-zereight-gitlab-mcp/retry-pipeline.md

WHAT IT DOES

What retry_pipeline does on Gitlab Mcp

AI agents invoke retry_pipeline to trigger actions in Gitlab 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.

RISK

Why retry_pipeline is rated High

Retrying a pipeline re-triggers execution of CI/CD jobs, which can run arbitrary code, deploy software, modify infrastructure, or consume compute resources. This is an Execute-category action as it triggers external operations whose effects depend on what the pipeline contains.

From the tool's definition Retry a failed or canceled pipeline

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs retry_pipeline safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Gitlab Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For retry_pipeline, this is the rule to start with:

retry_pipeline Rate-limited

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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "retry_pipeline": {
      "limits": [
        {
          "counter": "retry_pipeline_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Gitlab Mcp, apply this rule, and every retry_pipeline call is checked against it from then on.

FAQ

Questions about retry_pipeline

What does the retry_pipeline tool do? +

Retry a failed or canceled pipeline. It is categorised as a Execute tool in the Gitlab Mcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on retry_pipeline? +

Register the Gitlab MCP server in PolicyLayer and add a rule for 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 Mcp. Nothing to install.

What risk level is retry_pipeline? +

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

Can I rate-limit retry_pipeline? +

Yes. Add a rate_limit block to the 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.

How do I block retry_pipeline completely? +

Set action: deny in the PolicyLayer policy for 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.

What MCP server provides retry_pipeline? +

retry_pipeline is provided by the Gitlab MCP server (@zereight/mcp-gitlab). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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