Control VLC playback with actions: play, pause, stop, fullscreen.
AI agents invoke vlc_control to trigger actions in Vlc. 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 triggers external operations on a media player application (play, pause, stop, fullscreen). These are runtime actions that affect an external process (VLC), making it Execute category. The blast radius is low since it only controls local media playback with no data destruction, financial impact, or system-level consequences.
From the tool's definition Control VLC playback with actions: play, pause, stop, fullscreen
Documented attack patterns abuse exactly the kind of access vlc_control gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Vlc, and nothing reaches the server without passing your rules. This is the rule we recommend for vlc_control:
{
"version": "1",
"default": "deny",
"tools": {
"vlc_control": {
"limits": [
{
"counter": "vlc_control_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}vlc_control 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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Control VLC playback with actions: play, pause, stop, fullscreen. It is categorised as a Execute tool in the Vlc MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Vlc MCP server in PolicyLayer and add a rule for vlc_control: 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 Vlc. Nothing to install.
vlc_control 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 vlc_control 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 vlc_control. 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.
vlc_control is provided by the Vlc MCP server (piebro/vlc-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Vlc, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
8 Vlc tools catalogued and risk-classified — across an index of 43,000+ MCP servers.