Retrieve a broad performance summary for the authenticated channel covering views, watch time, subscriber changes, likes, dislikes, comments, and shares. Optionally break the data down by day or month. Args: - \
AI agents call youtube_channel_summary 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 queries and retrieves analytics data for the authenticated YouTube channel. It performs a read-only operation that returns performance metrics without creating, modifying, deleting, executing code, or moving money. Even though the server overall has destructive capabilities (e.g., youtube_delete_video), this specific tool is purely informational.
From the tool's definition Tool name 'youtube_channel_summary' and description 'Retrieve a broad performance summary' with 'views, watch time, subscriber changes, likes, dislikes, comments, and shares' indicates data retrieval with no modification or side effects.
Attacks that exploit this kind of access
Retrieve a broad performance summary for the authenticated channel covering views, watch time, subscriber changes, likes, dislikes, comments, and shares. Optionally break the data down by day or month. 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_channel_summary: 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_channel_summary 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_channel_summary 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_channel_summary. 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_channel_summary 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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