Retrieve detailed analytics for a single YouTube video, including views, watch time, retention, subscriber impact, engagement, and more. Optionally break down by day. Args: - \
AI agents call youtube_video_performance to retrieve information from Youtube without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only retrieves/queries analytics data for a YouTube video. It has no side effects, does not modify any data, and purely reads performance metrics. Severity is low because misuse only exposes analytics data with no destructive or financial impact.
From the tool's definition Retrieve detailed analytics for a single YouTube video, including views, watch time, retention, subscriber impact, engagement, and more
Attacks that exploit this kind of access
Retrieve detailed analytics for a single YouTube video, including views, watch time, retention, subscriber impact, engagement, and more. Optionally break down by day. Args: - \. It is categorised as a Read tool in the Youtube MCP Server, which means it retrieves data without modifying state.
Register the Youtube MCP server in PolicyLayer and add a rule for youtube_video_performance: 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 Youtube. Nothing to install.
youtube_video_performance 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 youtube_video_performance 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 youtube_video_performance. 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.
youtube_video_performance is provided by the Youtube MCP server (tuitamogamer-gpt/youtube-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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