timeout_workflow_steps

Scan all running workflow steps and mark those that have exceeded their timeout_seconds as FAILED, then advance the affected workflows. Designed to be called periodically.

SERVERTodo for AI MCP Server SOURCEtodo-for-ai/todo-for-ai-mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/todo-for-ai-todo-for-ai-mcp/timeout-workflow-steps.md

WHAT IT DOES

What timeout_workflow_steps does on Todo for AI MCP Server

AI agents call timeout_workflow_steps to retrieve information from Todo for AI MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why timeout_workflow_steps is rated Low

Even though timeout_workflow_steps only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs timeout_workflow_steps safely

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

timeout_workflow_steps Allowed

timeout_workflow_steps is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "timeout_workflow_steps": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Todo for AI MCP Server, apply this rule, and every timeout_workflow_steps call is checked against it from then on.

FAQ

Questions about timeout_workflow_steps

What does the timeout_workflow_steps tool do? +

Scan all running workflow steps and mark those that have exceeded their timeout_seconds as FAILED, then advance the affected workflows. Designed to be called periodically. It is categorised as a Read tool in the Todo for AI MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on timeout_workflow_steps? +

Register the Todo for AI MCP Server MCP server in PolicyLayer and add a rule for timeout_workflow_steps: 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 Todo for AI MCP Server. Nothing to install.

What risk level is timeout_workflow_steps? +

timeout_workflow_steps is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit timeout_workflow_steps? +

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

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

timeout_workflow_steps is provided by the Todo for AI MCP Server MCP server (todo-for-ai/todo-for-ai-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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