AI agents call youtube_comments to retrieve information from Outscraper MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves publicly available YouTube comment data with no side effects on the target platform. It is Read category. Severity is medium rather than low because bulk comment scraping could violate YouTube's Terms of Service, enable harassment by aggregating personal comments, or be used for sentiment manipulation.
From the tool's definition Tool name 'youtube_comments' indicates retrieval of comments from YouTube. Server context describes 'data extraction services' and 'web scraping tasks' for business intelligence.
Documented attack patterns abuse exactly the kind of access youtube_comments gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Outscraper MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for youtube_comments:
{
"version": "1",
"default": "deny",
"tools": {
"youtube_comments": {}
}
}youtube_comments is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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youtube_comments. It is categorised as a Read tool in the Outscraper MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Outscraper MCP Server MCP server in PolicyLayer and add a rule for youtube_comments: 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 Outscraper MCP Server. Nothing to install.
youtube_comments 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_comments 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_comments. 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_comments is provided by the Outscraper MCP Server MCP server (outscraper/outscraper-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Outscraper MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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28 Outscraper MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.