youtube-mcp
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct resource: transcript, video metadata, channel info, and search results. There is no overlap or ambiguity between them.
Naming Consistency4/5Most tools follow the get_<resource> pattern (get_transcript, get_video_info, get_channel_info), with search_videos as a minor deviation. The naming is still clear and predictable, but not perfectly uniform.
Tool Count5/5The server has 4 tools, which is well-scoped for a YouTube info retrieval MCP. Each tool serves a clear and necessary purpose without redundancy.
Completeness4/5The coverage is solid for a read-only YouTube API: search, video info, channel info, and transcripts. Minor gaps like playlist support or comments are not core to the apparent purpose, so agents can work around them.
Average 3.7/5 across 4 of 4 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
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This repository is licensed under MIT License.
This repository includes a README.md file.
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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?
No annotations are provided, so the description must carry full behavioral burden. It only states the basic action and does not disclose what the response contains, whether it returns a list, any sorting/filtering limitations, or other behavioral traits. For a tool with no annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant phrasing. Every word earns its place, and it is immediately clear what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only search tool with complete parameter schema, the description is minimally adequate. However, without an output schema, it does not explain what kind of results are returned (e.g., metadata fields, video IDs), and it lacks any context about limitations or the difference from sibling retrieval tools. It meets the baseline but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters (query and maxResults), so the baseline is 3. The description's mention of 'keyword' merely restates the query parameter and adds no additional semantic meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search') and resource ('YouTube videos') with a clear method ('by keyword'). It clearly distinguishes from sibling tools which all retrieve specific entities (transcript, video info, channel info) rather than performing discovery.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for finding videos by keyword, and sibling names suggest it is the discovery tool. However, it does not explicitly state when to use this tool over alternatives or mention any exclusions (e.g., 'use get_video_info for details on a specific video').
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 must carry the full burden of behavioral disclosure. It merely states 'Get information,' implying a read operation, but fails to mention auth requirements, potential rate limits, error behavior, or whether only public data is returned. This is a significant gap for a tool without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes meaning, listing the resource and the specific data points returned. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description is fairly complete: it specifies the channel identifier and the expected return content. However, it omits details like whether the response includes channel thumbnails, description, or other metadata, and does not clarify if 'recent uploads' means a list of video IDs or full video objects. Minor gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% since the only parameter, channelId, has a description ('YouTube channel ID'). The description adds no extra meaning beyond the schema, so the baseline of 3 applies. It does not clarify format, required scope, or valid values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with a clear resource ('information about a YouTube channel') and enumerates the data returned (subscriber count, video count, recent uploads). This clearly differentiates it from sibling tools like get_video_info, get_transcript, and search_videos, which target other aspects of YouTube data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly conveys when to use the tool (when channel-level info is needed) by listing channel-specific fields, but it does not explicitly state exclusions or alternatives. For example, a user may need get_video_info for video-specific details, but no such guidance is given.
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. It discloses the return content (title, description, view count, likes) but does not explicitly state that this is a read-only operation, mention authentication needs, or address potential errors/rate limits. The 'get' verb implies read-only, but more behavioral context could be added.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the primary purpose and lists specific example fields. Every word is useful, with no redundancy or tangents.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description provides a reasonable overview of the return content. However, it omits details like possible errors, authentication requirements, or the full extent of 'more' metadata, so it is not fully complete but adequate for a low-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for the single 'url' parameter, including that it accepts a URL or video ID. The description adds no additional parameter information, so the schema does the heavy lifting and the description provides no extra value here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get metadata') and resource ('YouTube video'), and enumerates concrete fields (title, description, view count, likes). It is easily distinguishable from sibling tools like get_transcript and get_channel_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving video metadata, but it does not explicitly discuss when to use it instead of alternatives, nor does it mention any exclusions or contextual prerequisites. The use case is implied rather than explicitly guided.
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?
No annotations are provided, so the description carries the burden of behavioral disclosure. It adds one non-obvious fact (no API key required) and 'Extract' implies a read operation, but it does not mention return format, rate limits, or error behavior. This is a minimal but not rich disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that states the action and a key context (no API key). Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters and no output schema, so the description must explain return values, but it does not. It states purpose and the no-API-key advantage but leaves the format of the extracted transcript (plain text, timestamps, etc.) unspecified. Adequate for a basic understanding, but incomplete for full autonomous use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters (url and lang) with descriptions and a default for lang, so schema coverage is 100%. The description itself adds no extra parameter meaning beyond what the schema provides, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Extract') with a clear resource ('transcript/subtitles from a YouTube video'). It immediately distinguishes itself from sibling tools like get_video_info, get_channel_info, and search_videos, which handle different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: extracts transcripts and works without an API key, which is a useful selection hint. However, it does not explicitly mention alternatives or state when not to use this tool, so it stops short of full exclusion guidance.
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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