After all tasks are done and approved, this tool finalizes the entire request. The user must call this to confirm that the request is fully completed.\n\n
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.
The tool creates or modifies data (marking a request as finalized/completed) in a reversible manner. It does not delete data (would be Destructive), execute arbitrary code (would be Execute), or move money (would be Financial). While it represents a significant workflow state change, it remains a Write operation as the state can theoretically be reverted or the record remains in the system with updated metadata.
From the tool's definition Tool description states it 'finalizes the entire request' and requires user confirmation of completion. This modifies the state of a request record from active to completed, which is a reversible state change rather than deletion.
Risk signalsBulk/mass operation — affects multiple targets
Documented attack patterns abuse exactly the kind of access approve_request_completion gives an agent:
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:
{
"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.
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After all tasks are done and approved, this tool finalizes the entire request. The user must call this to confirm that the request is fully completed.\n\n. 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.
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.
approve_request_completion is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
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.
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.
approve_request_completion is provided by the Mcp Taskmanager MCP server (kazuph/mcp-taskmanager). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mcp Taskmanager, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
10 Mcp Taskmanager tools catalogued and risk-classified — across an index of 43,000+ MCP servers.