replay_workflow_run

Replay or plan replay for a workflow run. Defaults to dry-run; live replay remains policy/audit gated.

SERVERStarfield SOURCE@adrata/starfield-mcp

High RISK CLASS

Category Execute

Parameters 31 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/adrata-starfield-mcp/replay-workflow-run.md

WHAT IT DOES

What replay_workflow_run does on Starfield

AI agents invoke replay_workflow_run to trigger actions in Starfield. 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.

Parameter	Type	Required	Description
`runId`	string	Yes	Workflow run id
`dryRun`	boolean	—	Defaults to true. Set false only for a live replay request.
`reason`	string	—	Why replay is being requested

Parameters from the server's own tool schema.

RISK

Why replay_workflow_run is rated High

replay_workflow_run triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs replay_workflow_run safely

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

replay_workflow_run Rate-limited

replay_workflow_run 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": {
    "replay_workflow_run": {
      "limits": [
        {
          "counter": "replay_workflow_run_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 Starfield, apply this rule, and every replay_workflow_run call is checked against it from then on.

FAQ

Questions about replay_workflow_run

What does the replay_workflow_run tool do? +

Replay or plan replay for a workflow run. Defaults to dry-run; live replay remains policy/audit gated. It is categorised as a Execute tool in the Starfield MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does replay_workflow_run accept? +

replay_workflow_run accepts 3 parameters: runId, dryRun, reason. Required: runId. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on replay_workflow_run? +

Register the Starfield MCP server in PolicyLayer and add a rule for replay_workflow_run: 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 Starfield. Nothing to install.

What risk level is replay_workflow_run? +

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

Can I rate-limit replay_workflow_run? +

Yes. Add a rate_limit block to the replay_workflow_run 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 replay_workflow_run completely? +

Set action: deny in the PolicyLayer policy for replay_workflow_run. 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 replay_workflow_run? +

replay_workflow_run is provided by the Starfield MCP server (@adrata/starfield-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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