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tejas-borate-wai

YouTube Insights MCP Server

by tejas-borate-wai
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation2/5

    The tools have overlapping purposes, as get_youtube_insights includes metadata and transcript, making it ambiguous when to choose get_youtube_metadata or get_youtube_transcript instead. This overlap can lead to misselection, as agents might use the comprehensive tool unnecessarily or struggle to pick the right specialized one.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with 'get_youtube_' prefix, using snake_case uniformly. This predictability makes it easy for agents to understand and navigate the tool set without confusion.

    Tool Count3/5

    With only 3 tools, the set feels thin for a 'YouTube Insights' server, as it lacks operations like search, list, or update capabilities that might be expected for broader video analysis. However, it covers basic retrieval functions, making it borderline appropriate but limited in scope.

    Completeness2/5

    There are significant gaps in the tool surface for a YouTube insights domain, such as no search tools for finding videos, no playlist or channel operations, and no update or deletion capabilities. The tools only provide read-only access to individual videos, which is insufficient for comprehensive insights workflows.

  • Average 3.3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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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 what the tool returns (transcript, metadata, summary) but lacks critical details: whether this requires API keys or authentication, rate limits, error handling, or if it's a read-only operation. For a tool fetching external data, 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 that front-loads the core purpose. Every word earns its place, with no redundancy or unnecessary elaboration, making it easy for an agent to parse quickly.

    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 tool's complexity (fetching and processing YouTube data) and lack of annotations and output schema, the description is incomplete. It doesn't explain return formats, error cases, or behavioral constraints, leaving the agent with insufficient context for reliable invocation.

    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 100%, so the schema already documents all parameters (url, languages, summary_sentences) with descriptions and defaults. The description adds no additional parameter semantics beyond implying the tool processes a YouTube video URL, which is already covered by the schema.

    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 tool's purpose: 'Get comprehensive insights from a YouTube video including transcript, metadata, and a brief summary.' It specifies the verb ('Get'), resource ('YouTube video'), and scope ('insights'), but doesn't explicitly differentiate from sibling tools like get_youtube_metadata and get_youtube_transcript, which likely provide more limited outputs.

    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 (get_youtube_metadata and get_youtube_transcript). It doesn't mention prerequisites, alternatives, 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 the full burden of behavioral disclosure. It states the tool retrieves metadata but does not cover critical aspects such as rate limits, authentication needs, error handling, or response format. This leaves significant gaps for a tool that interacts with an external service like YouTube.

    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 that front-loads the core purpose and includes specific examples of metadata fields. There is no wasted verbiage, making it highly concise and well-structured for quick understanding.

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

    Completeness3/5

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

    Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits and usage context, which are important for external API interactions. Without an output schema, it also does not explain return values, though this is not required.

    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, clearly documenting the 'url' parameter as accepting a 'YouTube video URL or video ID'. The description does not add any semantic details beyond this, so it meets the baseline score of 3 where the schema does the heavy lifting.

    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 tool's purpose with a specific verb ('Get') and resource ('metadata for a YouTube video'), and lists key metadata fields (title, author, thumbnail). However, it does not explicitly differentiate from sibling tools like 'get_youtube_insights' or 'get_youtube_transcript', which likely retrieve different types of video information.

    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 (e.g., 'get_youtube_insights' for analytics or 'get_youtube_transcript' for text content). It implies usage for basic video metadata but lacks explicit context, alternatives, or exclusions, 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.

  • Behavior3/5

    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 describes the core functionality (extracting transcripts) and input flexibility (various URL formats/video IDs), but doesn't mention potential limitations like availability of transcripts, error handling, rate limits, or authentication requirements. It adds some context but lacks comprehensive behavioral details.

    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 perfectly concise with two sentences that each earn their place: the first states the core purpose, the second clarifies input flexibility. It's front-loaded with the main functionality and wastes no words on unnecessary details.

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

    Completeness3/5

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

    Given 2 parameters with 100% schema coverage but no annotations and no output schema, the description provides adequate basic context but could do more. It explains what the tool does and input formats, but doesn't address output format, error conditions, or limitations. For a tool with no annotations or output schema, this leaves some gaps in understanding the complete behavior.

    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 100%, so the schema already fully documents both parameters (url and languages). The description adds no additional parameter semantics beyond what's in the schema - it mentions URL formats/video IDs and transcript extraction, but doesn't provide syntax examples, format details, or language handling beyond the schema's default explanation. Baseline 3 is appropriate when schema does the heavy lifting.

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

    Purpose5/5

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

    The description clearly states the specific action ('Extract the full transcript') and resource ('from a YouTube video'), distinguishing it from sibling tools like get_youtube_insights and get_youtube_metadata. It provides a precise verb+resource combination that leaves no ambiguity about the tool's function.

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

    Usage Guidelines4/5

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

    The description implicitly suggests usage for transcript extraction from YouTube videos, but it doesn't explicitly state when to use this tool versus alternatives like get_youtube_insights or get_youtube_metadata. It provides clear context about supported inputs (URL formats or video IDs) but lacks explicit guidance on tool selection among siblings.

    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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