AI agents invoke join_meeting 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.
Joining a meeting is an external operation that triggers participation in a live video call. The description is empty, but given the server context, this tool initiates an active session in a real-time meeting environment. This constitutes an Execute-level action with high blast radius since an AI agent could autonomously join calls, potentially exposing conversations or impersonating users.
From the tool's definition Tool name 'join_meeting' on a server described as enabling AI agents to 'join and actively participate in video calls' — sibling tools include speak_text, send_chat_message, share_screen, leave_meeting
Documented attack patterns abuse exactly the kind of access join_meeting 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 join_meeting:
{
"version": "1",
"default": "deny",
"tools": {
"join_meeting": {
"limits": [
{
"counter": "join_meeting_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}join_meeting 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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join_meeting. 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 join_meeting: 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.
join_meeting 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 join_meeting 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 join_meeting. 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.
join_meeting 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.