run-rerun

Re-runs a workflow run by ID. Optionally re-runs only failed jobs or a specific job. Returns structured result with run ID, status, and URL.

SERVERDocker SOURCE@paretools/docker

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-dave-london-docker/run-rerun.md

WHAT IT DOES

What run-rerun does on Docker

AI agents invoke run-rerun to trigger actions in Docker. 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 run-rerun is rated High

This tool triggers the execution of CI/CD workflows/jobs, which can run arbitrary code, deploy applications, or modify systems depending on the workflow definition. While the tool itself does not directly delete or move money, it executes external operations whose outcomes depend on arguments (which run/jobs to re-trigger).

From the tool's definition 'Re-runs a workflow run by ID' and 'optionally re-runs only failed jobs or a specific job' indicates triggering external CI/CD pipeline execution whose effects depend on the workflow content and argument selection.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs run-rerun safely

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

run-rerun Rate-limited

run-rerun 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": {
    "run-rerun": {
      "limits": [
        {
          "counter": "run-rerun_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 Docker, apply this rule, and every run-rerun call is checked against it from then on.

FAQ

Questions about run-rerun

What does the run-rerun tool do? +

Re-runs a workflow run by ID. Optionally re-runs only failed jobs or a specific job. Returns structured result with run ID, status, and URL. It is categorised as a Execute tool in the Docker MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on run-rerun? +

Register the Docker MCP server in PolicyLayer and add a rule for run-rerun: 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 Docker. Nothing to install.

What risk level is run-rerun? +

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

Can I rate-limit run-rerun? +

Yes. Add a rate_limit block to the run-rerun 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 run-rerun completely? +

Set action: deny in the PolicyLayer policy for run-rerun. 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 run-rerun? +

run-rerun is provided by the Docker MCP server (@paretools/docker). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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