Skip to main content
Glama
instructa

YouTube Music MCP

by instructa
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation2/5

    The two tools have overlapping purposes that could cause confusion. Both 'playTrack' and 'searchTrack' involve searching for tracks on YouTube Music, with 'playTrack' additionally opening the top result in a browser. An agent might misselect between them when the intent is ambiguous, such as wanting to search without playing or vice versa, as the descriptions don't clearly delineate distinct use cases.

    Naming Consistency5/5

    The tool names follow a consistent pattern throughout. Both use camelCase with a verb-noun structure ('playTrack' and 'searchTrack'), making them predictable and readable. There are no deviations or mixed conventions, which aids in clarity and usability.

    Tool Count2/5

    The tool count of 2 feels too thin for a YouTube Music server's apparent scope. With only search and play functionality, there are obvious gaps like managing playlists, controlling playback, or accessing user data. This limited set may hinder agents from performing common music-related tasks, indicating an incomplete surface for the domain.

    Completeness2/5

    The tool surface is severely incomplete for a YouTube Music domain. It only covers searching and playing tracks, missing essential operations such as pausing, skipping, volume control, playlist management, or user authentication. These gaps will likely cause agent failures when attempting broader music interactions, as the current tools don't support a full lifecycle or common workflows.

  • Average 3.5/5 across 2 of 2 tools scored. Lowest: 2.9/5.

    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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 carries the full burden. It states the tool searches, implying a read-only operation, but does not disclose behavioral traits like rate limits, authentication needs, result format, pagination, or error handling. For a search 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 waste. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary details.

    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 does not explain what the search returns (e.g., list of tracks, metadata), how results are structured, or any limitations. For a search tool, this leaves critical context gaps for an AI 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 schema description coverage is 100%, with the parameter 'trackName' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, such as search syntax or examples. Baseline 3 is appropriate when 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: 'Search for tracks on YouTube Music by name.' It specifies the verb ('search'), resource ('tracks'), and platform ('YouTube Music'), but does not explicitly differentiate from its sibling tool 'playTrack'. This makes it clear but not fully sibling-aware.

    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. It does not mention the sibling tool 'playTrack' or any other search methods, nor does it specify prerequisites or exclusions. This leaves usage context entirely implicit.

    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 that the tool opens the top result in the default browser, which is useful behavioral context, but does not mention potential side effects like browser pop-ups, authentication needs, or rate limits.

    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 action without any wasted words, making it easy to understand quickly.

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

    Completeness4/5

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

    Given the tool's moderate complexity (searching and opening in browser) with no annotations or output schema, the description is reasonably complete but lacks details on error handling, what happens if no results are found, or the format of any potential output.

    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 the 'trackName' parameter. The description adds no additional meaning beyond implying the parameter is used for searching, which aligns with the schema's description.

    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 ('search for a track on YouTube Music and open the top result in the default browser') with the resource ('track'), distinguishing it from the sibling tool 'searchTrack' which presumably only searches without opening.

    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 implies usage for playing tracks via YouTube Music, but does not explicitly state when to use this tool versus 'searchTrack' or other alternatives, nor does it provide exclusions or prerequisites.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

mcp-youtube-music MCP server

Copy to your README.md:

Score Badge

mcp-youtube-music MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/instructa/mcp-youtube-music'

If you have feedback or need assistance with the MCP directory API, please join our Discord server