search_transcript
AI agents call search_transcript to retrieve information from YouTube Transcript MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool searches through transcript data to retrieve matching content. Searching is a read operation with no side effects—it queries existing transcripts without modifying, deleting, or executing code. The empty description lowers confidence slightly, but the server's stated purpose (fetching and analyzing) and the presence of parallel read-only sibling tools support classification as Read.
From the tool's definition Tool name 'search_transcript' combined with server description stating it 'Enables fetching, searching, and analyzing YouTube video transcripts' indicates a read-only query operation.
Attacks that exploit this kind of access
search_transcript. It is categorised as a Read tool in the YouTube Transcript MCP Server MCP Server, which means it retrieves data without modifying state.
Register the YouTube Transcript MCP Server MCP server in PolicyLayer and add a rule for search_transcript: 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 Transcript MCP Server. Nothing to install.
search_transcript 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 search_transcript 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 search_transcript. 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.
search_transcript is provided by the YouTube Transcript MCP Server MCP server (suckerfish/yttranscript_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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