AI agents invoke stop_replay_buffer to trigger actions in OBS MCP Server. 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.
This tool executes a command that halts an ongoing operation (replay buffer) in OBS Studio. While not destructive (the buffer can be restarted), it does affect the state of a running system and constitutes an action with external effects. It does not retrieve data (Read), create/modify persistent data reversibly (Write), or involve financial transactions.
From the tool's definition The tool 'stop_replay_buffer' stops the replay buffer output in OBS Studio. This is an active operation that triggers a state change in an external system (OBS), controlling media recording/playback functionality.
Documented attack patterns abuse exactly the kind of access stop_replay_buffer gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and OBS MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for stop_replay_buffer:
{
"version": "1",
"default": "deny",
"tools": {
"stop_replay_buffer": {
"limits": [
{
"counter": "stop_replay_buffer_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} stop_replay_buffer 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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Stops the replay buffer output. It is categorised as a Execute tool in the OBS MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the OBS MCP Server MCP server in PolicyLayer and add a rule for stop_replay_buffer: 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 OBS MCP Server. Nothing to install.
stop_replay_buffer 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 stop_replay_buffer 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 stop_replay_buffer. 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.
stop_replay_buffer is provided by the OBS MCP Server MCP server (royshil/obs-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 200 OBS MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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200 OBS MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.