Youtube Mp36 MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined as converting to MP3 at a default bit rate, making it distinct by default.
Naming Consistency5/5The single tool name 'get_mp3' follows a clear verb_noun pattern (get + mp3), which is consistent and predictable. Since there is only one tool, there is no inconsistency to evaluate.
Tool Count2/5A single tool is too few for a server named 'Youtube Mp36 MCP Server', which implies a broader scope for YouTube MP3-related operations. This minimal set feels thin and underdeveloped for the apparent domain, limiting functionality to just conversion without other expected features like search, download options, or metadata handling.
Completeness2/5The tool surface is severely incomplete for a YouTube MP3 server. It only provides conversion to MP3 at a default bit rate, missing obvious operations such as searching for videos, specifying bit rates, handling playlists, or retrieving metadata. This will likely cause agent failures when trying to perform common tasks in this domain.
Average 3.2/5 across 1 of 1 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 is passing
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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses quota costs based on file length, which is a key behavioral trait (resource consumption). However, it lacks details on other aspects like error handling, rate limits, authentication needs, or what happens during conversion (e.g., is it destructive to the original?). It adds some value but is incomplete for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that directly address conversion and quota costs. It is front-loaded with the main purpose. However, the second sentence could be more structured, and it slightly repeats quota info from the schema, but overall it's efficient with minimal waste.
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?
Given no annotations, no output schema, and a mutation tool (conversion), the description is moderately complete. It covers purpose and quota costs, but misses details like return values, error conditions, or full behavioral context. It's adequate as a minimum viable description but has clear gaps for a tool with parameters and potential side effects.
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%, so the schema already documents all parameters thoroughly. The description does not add any meaning beyond what the schema provides regarding parameters; it only mentions quota costs generally. Baseline is 3 when schema does the heavy lifting, and the description doesn't compensate with extra insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Convert to MP3 at the default bit rate.' It specifies the action (convert) and resource (to MP3), but lacks differentiation from siblings since none exist, so it can't achieve a perfect score. The description is specific and not tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It mentions quota costs, which might imply usage considerations, but does not explicitly state when or why to invoke it, nor does it address prerequisites or exclusions. Without siblings, this is less critical, but still a gap.
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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