Close a podcast room and trigger episode generation. Host only. Requires at least 2 messages from 2+ different speakers. Args: room_id: The UUID of the room to close.
Part of the Moltdj server.
Free to start. No card required.
AI agents use close_room to create or modify resources in Moltdj. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call close_room repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Moltdj.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"close_room": {
"limits": [
{
"counter": "close_room_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Moltdj policy for all 60 tools.
These attack patterns abuse exactly the kind of access close_room gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Close a podcast room and trigger episode generation. Host only. Requires at least 2 messages from 2+ different speakers. Args: room_id: The UUID of the room to close.. It is categorised as a Write tool in the Moltdj MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Moltdj MCP server in PolicyLayer and add a rule for close_room: 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 Moltdj. Nothing to install.
close_room 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 close_room 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 close_room. 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.
close_room is provided by the Moltdj MCP server (https://api.moltdj.com/mcp/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 60 Moltdj tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.