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jerroldneal

MCP Browser YouTube Transcript

by jerroldneal
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JavaScript
Remote

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_timed_transcript retrieves transcript with timestamps, get_transcript retrieves plain text transcript, and get_video_info fetches metadata. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case (get_timed_transcript, get_transcript, get_video_info). The naming is predictable and uniform throughout the set.

    Tool Count4/5

    Three tools is appropriate for the server's purpose of accessing YouTube transcripts and video info, though it feels slightly minimal. Each tool earns its place, but there might be room for additional related functions like search or list operations.

    Completeness4/5

    The toolset covers the core needs for YouTube transcript and video metadata access well, with no obvious dead ends. However, there are minor gaps such as the inability to search for videos or handle playlist transcripts, which agents might need to work around.

  • Average 2.9/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions fetching a transcript with timestamps but omits critical details such as authentication needs, rate limits, error handling, or what the output format looks like (e.g., structured data vs. raw text). This is inadequate for a tool with multiple parameters and no output schema.

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

    Conciseness5/5

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

    The description is extremely concise with a single sentence that front-loads the core purpose. There is no wasted language or redundancy, making it efficient for quick understanding.

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

    Completeness2/5

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

    Given the complexity (4 parameters, low schema coverage, no annotations, no output schema), the description is incomplete. It fails to address key aspects like parameter usage, behavioral traits, or output expectations, leaving significant gaps for the agent to operate effectively.

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

    Parameters2/5

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

    Schema description coverage is low (25%), with only the 'url' parameter documented. The description does not compensate by explaining the semantics of 'lang', 'start', or 'end' parameters, leaving them undocumented. It implies timestamps but doesn't clarify if 'start' and 'end' relate to time ranges or other units.

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

    Purpose4/5

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

    The description clearly states the action ('fetches') and resource ('transcript with timestamps'), distinguishing it from sibling tools like 'get_transcript' (likely without timestamps) and 'get_video_info' (different resource). However, it doesn't specify the source (YouTube) or fully differentiate from siblings beyond the timestamp aspect.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives like 'get_transcript' or 'get_video_info'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage based on tool names alone.

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

  • Behavior2/5

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

    With no annotations provided, the description carries full burden but only states what the tool does ('fetches'), not behavioral traits like authentication needs, rate limits, error handling, or output format. It doesn't disclose if this is a read-only operation or has side effects, which is a significant gap for a tool with no annotation coverage.

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

    Conciseness5/5

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

    The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.

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

    Completeness2/5

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

    Given no annotations, no output schema, and incomplete parameter documentation (50% coverage), the description is inadequate. It doesn't explain return values, error conditions, or behavioral nuances, leaving significant gaps for a tool that fetches data from an external source like YouTube.

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

    Parameters3/5

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

    Schema description coverage is 50% (only 'url' has a description), and the description adds no parameter-specific information beyond implying a YouTube video URL is needed. It doesn't explain the 'lang' parameter or provide context beyond what the schema minimally offers, so it meets the baseline but doesn't compensate for the coverage gap.

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

    Purpose4/5

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

    The description clearly states the action ('fetches') and resource ('plain text transcript of a YouTube video'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like get_timed_transcript, which likely provides timestamped transcripts, so it misses full sibling distinction.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives like get_timed_transcript or get_video_info. There's no mention of prerequisites, exclusions, or specific contexts for usage, leaving the agent to infer based on tool names alone.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'fetches' implies a read operation, it doesn't specify whether this requires authentication, has rate limits, returns partial/full metadata, or handles errors. For a tool with zero annotation coverage, this is a significant gap.

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

    Conciseness5/5

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

    The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the core purpose without unnecessary elaboration.

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

    Completeness2/5

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

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what metadata is returned (e.g., title, duration, uploader), potential errors, or behavioral constraints. For a tool fetching video metadata, this leaves critical gaps for an agent.

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

    Parameters3/5

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

    The input schema has 100% description coverage, with the 'url' parameter clearly documented. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline score of 3 for high schema coverage.

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

    Purpose4/5

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

    The description clearly states the verb ('fetches') and resource ('metadata about the video'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings (get_timed_transcript and get_transcript), which appear to be related but serve different functions.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus its siblings or alternatives. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the tool name alone.

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

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