Resume paused audio playback on the glasses.
AI agents invoke fw_resume to trigger actions in Crow. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool triggers an external operation (resuming audio playback on a hardware device - glasses). It executes an action on a physical/external device, making it Execute category. The blast radius is low as it only affects audio playback state on a wearable device.
From the tool's definition Resume paused audio playback on the glasses
Documented attack patterns abuse exactly the kind of access fw_resume gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Crow, and nothing reaches the server without passing your rules. This is the rule we recommend for fw_resume:
{
"version": "1",
"default": "deny",
"tools": {
"fw_resume": {
"limits": [
{
"counter": "fw_resume_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} fw_resume stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Resume paused audio playback on the glasses. It is categorised as a Execute tool in the Crow MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Crow MCP server in PolicyLayer and add a rule for fw_resume: 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 Crow. Nothing to install.
fw_resume is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the fw_resume 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 fw_resume. 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.
fw_resume is provided by the Crow MCP server (kh0pper/crow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Crow, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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576 Crow tools catalogued and risk-classified — across an index of 43,000+ MCP servers.