Medium Risk

approve_request_completion

Approve the completion of an entire request.

How to control approve_request_completion ↓

What approve_request_completion does on MCP TaskManager

AI agents use approve_request_completion to create or update resources in MCP TaskManager — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP TaskManager environment.

Medium Risk

Why approve_request_completion needs a policy

The tool changes request status irreversibly in workflow terms (marks completion), but the action itself is reversible—a request could theoretically be reopened or its completion revoked by another action. This is consistent with Write category (creates or modifies data reversibly) rather than Destructive.

From the tool's definition Tool is named 'approve_request_completion' and described as 'Approve the completion of an entire request.' This action modifies the state of a request object from pending/in-progress to completed, which is a reversible state change.

Risk signalsBulk/mass operation — affects multiple targets

Documented attack patterns abuse exactly the kind of access approve_request_completion gives an agent:

How to control approve_request_completion

PolicyLayer is an MCP gateway — it sits between your AI agents and MCP TaskManager, and nothing reaches the server without passing your rules. This is the rule we recommend for approve_request_completion:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "approve_request_completion": {
      "limits": [
        {
          "counter": "approve_request_completion_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

approve_request_completion stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

  1. Create a free account and register MCP TaskManager — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
LIMIT THIS TOOL →

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Related tools and policies

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Questions about approve_request_completion

What does the approve_request_completion tool do? +

Approve the completion of an entire request. It is categorised as a Write tool in the MCP TaskManager MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on approve_request_completion? +

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

What risk level is approve_request_completion? +

approve_request_completion is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit approve_request_completion? +

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

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

approve_request_completion is provided by the MCP TaskManager MCP server (rudra-ravi/mcp-taskmanager). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every MCP TaskManager tool call.

Start from MCP TaskManager, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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