AI agents call get_participants to retrieve information from Joinly without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves participant information from an active video call with no ability to modify, delete, or execute actions. While the description is empty, the name and context clearly indicate a simple query/list operation. Blast radius is minimal—misuse would only expose meeting participant data, not enable harmful modifications or actions.
From the tool's definition Tool name 'get_participants' indicates a retrieval operation. Given the context of video call management tools (join_meeting, leave_meeting, etc.), this tool retrieves the list of participants in a meeting—a read-only operation with no side effects.
Documented attack patterns abuse exactly the kind of access get_participants 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 get_participants:
{
"version": "1",
"default": "deny",
"tools": {
"get_participants": {}
}
}get_participants is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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get_participants. It is categorised as a Read tool in the Joinly MCP Server, which means it retrieves data without modifying state.
Register the Joinly MCP server in PolicyLayer and add a rule for get_participants: 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.
get_participants is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_participants 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 get_participants. 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.
get_participants 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.