Mark a task as completed
AI agents use mark_task_completed to create or update resources in A2AMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your A2AMCP environment.
The tool modifies existing data (marks a task as completed) in a Redis-backed coordination system. This is a Write operation because it creates or modifies data reversibly. While it affects a shared state used by multiple agents, the change is not destructive (the task record persists), not executable (no code/commands), and not financial.
From the tool's definition Tool name 'mark_task_completed' and description 'Mark a task as completed' indicate modification of task state in a shared coordination system. This changes data (task status) but is reversible—tasks can be unmarked or recreated.
Documented attack patterns abuse exactly the kind of access mark_task_completed gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and A2AMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for mark_task_completed:
{
"version": "1",
"default": "deny",
"tools": {
"mark_task_completed": {
"limits": [
{
"counter": "mark_task_completed_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}mark_task_completed 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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Mark a task as completed. It is categorised as a Write tool in the A2AMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the A2A MCP server in PolicyLayer and add a rule for mark_task_completed: 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 A2AMCP. Nothing to install.
mark_task_completed 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 mark_task_completed 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 mark_task_completed. 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.
mark_task_completed is provided by the A2A MCP server (webdevtodayjason/a2amcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from A2AMCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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17 A2AMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.