retry_execution

Retry a failed workflow execution using the same inputs. Creates a new execution.

SERVERFlowDot MCP Server SOURCEflowdot-llc/mcp-server

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/flowdot-llc-mcp-server/retry-execution.md

WHAT IT DOES

What retry_execution does on FlowDot MCP Server

AI agents invoke retry_execution to trigger actions in FlowDot MCP Server. 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_execution is rated High

This tool triggers a new workflow execution, which constitutes running an external operation. While it reuses prior inputs, it still initiates a new execution that may have side effects depending on the workflow's actions. This falls under Execute rather than Write since it runs/triggers a workflow rather than simply creating or modifying a data record.

From the tool's definition 'Retry a failed workflow execution using the same inputs. Creates a new execution.'

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs retry_execution safely

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

retry_execution Rate-limited

retry_execution 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_execution": {
      "limits": [
        {
          "counter": "retry_execution_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 FlowDot MCP Server, apply this rule, and every retry_execution call is checked against it from then on.

FAQ

Questions about retry_execution

What does the retry_execution tool do? +

Retry a failed workflow execution using the same inputs. Creates a new execution. It is categorised as a Execute tool in the FlowDot MCP Server 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_execution? +

Register the FlowDot MCP Server MCP server in PolicyLayer and add a rule for retry_execution: 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 FlowDot MCP Server. Nothing to install.

What risk level is retry_execution? +

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

Can I rate-limit retry_execution? +

Yes. Add a rate_limit block to the retry_execution 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_execution completely? +

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

retry_execution is provided by the FlowDot MCP Server MCP server (flowdot-llc/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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