YouTube Transcript MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it fetches transcripts (implying read-only, non-destructive), uses yt-dlp (implementation detail), and returns 'Complete transcript data with metadata'. However, it lacks details on error handling, rate limits, authentication needs, or what 'metadata' includes, leaving gaps for a tool with 5 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized. It front-loads the core purpose in the first sentence, followed by a clear 'Args' and 'Returns' section with bullet-like formatting. Every sentence adds value without redundancy, making it easy to scan and understand.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters, no annotations, and no output schema, the description does a strong job covering inputs and basic behavior. However, it lacks details on output structure (beyond 'metadata'), error cases, or performance aspects, which could be important for a tool fetching external data. It's mostly complete but has minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate fully. It adds significant meaning beyond the schema by explaining each parameter's purpose and usage: video_id accepts 'ID or URL', language_code uses 'auto-detected' as default, preserve_formatting affects 'timestamp formatting in plain text', and start_time/end_time 'filter transcript'. This effectively documents all 5 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Fetch the transcript') and resource ('for a YouTube video'), using the implementation detail 'using yt-dlp' for additional context. It distinguishes itself from siblings like get_available_languages (lists languages), get_transcript_summary (summarizes), and search_transcript (searches within transcripts).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through parameter descriptions (e.g., 'Optional language code', 'Optional start time'), suggesting when to use certain features, but lacks explicit guidance on when to choose this tool over alternatives like get_transcript_summary or search_transcript. No clear exclusions or prerequisites are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.