Once the assistant has marked a task as done using
AI agents use approve_task_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.
Approving task completion is a state-change operation that modifies the task's status in the queue system. It is reversible in principle (status can be changed back) and does not delete data, execute code, or involve finances. The description is truncated/incomplete, which lowers confidence slightly, but the name and context clearly indicate a write/state-update operation.
From the tool's definition 'approve_task_completion' - approves a task that has been marked as done
Documented attack patterns abuse exactly the kind of access approve_task_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_task_completion:
{
"version": "1",
"default": "deny",
"tools": {
"approve_task_completion": {
"limits": [
{
"counter": "approve_task_completion_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} approve_task_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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Once the assistant has marked a task as done using. 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_task_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_task_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_task_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_task_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_task_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.
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