AI agents use send_chat_message to create or update resources in Joinly — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Joinly environment.
This tool creates new chat messages during video calls, which is a Write operation with reversible effects (messages can typically be deleted/edited). Severity is medium because misuse could spam, harass, or manipulate meeting participants, but the blast radius is limited to the specific meeting rather than external systems.
From the tool's definition Tool name 'send_chat_message' indicates creation/modification of chat data in a real-time communication context.
Documented attack patterns abuse exactly the kind of access send_chat_message 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 send_chat_message:
{
"version": "1",
"default": "deny",
"tools": {
"send_chat_message": {
"limits": [
{
"counter": "send_chat_message_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}send_chat_message 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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send_chat_message. It is categorised as a Write tool in the Joinly MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Joinly MCP server in PolicyLayer and add a rule for send_chat_message: 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.
send_chat_message 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 send_chat_message 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 send_chat_message. 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.
send_chat_message 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.