Collect transcripts, metadata, and optional comments for specific videos.
AI agents call analyze_videos to retrieve information from Youtube Research without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and aggregates existing data from YouTube (transcripts, metadata, comments) for analysis purposes. It performs read-only operations with no side effects on YouTube or the user's data. The blast radius of misuse is minimal—an agent could retrieve sensitive information from public videos, but cannot modify, delete, or execute operations.
From the tool's definition Tool 'analyze_videos' collects transcripts, metadata, and optional comments for specific videos. Keywords: 'collect', 'transcripts', 'metadata', 'comments' all indicate data retrieval with no modification or deletion.
Documented attack patterns abuse exactly the kind of access analyze_videos gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Youtube Research, and nothing reaches the server without passing your rules. This is the rule we recommend for analyze_videos:
{
"version": "1",
"default": "deny",
"tools": {
"analyze_videos": {}
}
}analyze_videos is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Collect transcripts, metadata, and optional comments for specific videos. It is categorised as a Read tool in the Youtube Research MCP Server, which means it retrieves data without modifying state.
Register the Youtube Research MCP server in PolicyLayer and add a rule for analyze_videos: 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 Research. Nothing to install.
analyze_videos 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 analyze_videos 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 analyze_videos. 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.
analyze_videos is provided by the Youtube Research MCP server (lee-s-dev/youtube-research-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Youtube Research, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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10 Youtube Research tools catalogued and risk-classified — across an index of 43,000+ MCP servers.