AI agents use update_task to create or update resources in LunaTask MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your LunaTask MCP Server environment.
The tool updates task records reversibly without deleting or destroying data. While the description is empty, the name combined with the server's stated capability to update productivity data and the pattern of similar tools (create_task for Write, delete_task for Destructive) clearly positions this as a Write operation.
From the tool's definition Tool name 'update_task' indicates modification of task data. Server description states the bridge 'supports creating and updating productivity data'.
Documented attack patterns abuse exactly the kind of access update_task gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and LunaTask MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_task:
{
"version": "1",
"default": "deny",
"tools": {
"update_task": {
"limits": [
{
"counter": "update_task_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_task 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.
Free to start. No card required.
update_task. It is categorised as a Write tool in the LunaTask MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the LunaTask MCP Server MCP server in PolicyLayer and add a rule for update_task: 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 LunaTask MCP Server. Nothing to install.
update_task 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 update_task 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 update_task. 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.
update_task is provided by the LunaTask MCP Server MCP server (tensorfreitas/lunatask-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from LunaTask MCP Server, 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.
12 LunaTask MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.