AI agents invoke unmute_yourself to trigger actions in Joinly. 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.
Unmuting in a video call is an external operation that changes the agent's audio state, potentially broadcasting audio to all meeting participants. This is an Execute-level action (triggers an external operation with real effects), with medium severity since it could inadvertently broadcast audio in a live meeting. Confidence is reduced due to the empty description.
From the tool's definition Tool name 'unmute_yourself' implies triggering an external operation (changing audio state in a live video call). Description is empty, lowering confidence.
Documented attack patterns abuse exactly the kind of access unmute_yourself gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Joinly, and nothing reaches the server without passing your rules. This is the rule we recommend for unmute_yourself:
{
"version": "1",
"default": "deny",
"tools": {
"unmute_yourself": {
"limits": [
{
"counter": "unmute_yourself_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}unmute_yourself 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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unmute_yourself. It is categorised as a Execute tool in the Joinly MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Joinly MCP server in PolicyLayer and add a rule for unmute_yourself: 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 Joinly. Nothing to install.
unmute_yourself 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 unmute_yourself 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 unmute_yourself. 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.
unmute_yourself is provided by the Joinly MCP server (joinly-ai/joinly). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Joinly, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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12 Joinly tools catalogued and risk-classified — across an index of 43,000+ MCP servers.