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elestirelbilinc-sketch

Media-infrastructure

by elestirelbilinc-sketch
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

generate_music

Create AI-generated music from text descriptions using Suno V5. Specify genre, mood, instruments, tempo, and vocal style to produce custom audio tracks.

Instructions

Generate AI music from text description using VAP (Suno V5). Returns a task ID for async tracking. Cost: $0.68.

IMPORTANT: Send ONLY the music description. Do NOT include any instructions or meta-text.

Describe: genre, mood, instruments, tempo, vocal style (or specify instrumental).

Example prompt: "Upbeat indie folk song with acoustic guitar, warm vocals, and light percussion. Feel-good summer vibes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesMusic description (200-500 chars recommended). Include genre, mood, instruments, tempo.
instrumentalNoGenerate without vocals (instrumental only)
durationNoTarget duration in seconds (30-480, default 120 = 2 min)
loudness_presetNoLoudness normalization. streaming=-14 LUFS (YouTube/Spotify), apple=-16 LUFS, broadcast=-23 LUFS (TV/EBU R128)streaming
audio_formatNoOutput format. WAV for enterprise/lossless (+$0.10)mp3

Implementation Reference

  • mcp/vap_mcp_proxy.py:191-218 (handler)
    The tool call handler which routes 'generate_music' to the default make_request fallback (line 214). Other specific tools like 'generate_video' are handled in custom functions.
    def handle_tools_call(params: Dict) -> Dict:
    """
    Handle tools/call request.

    Directive #240: Special handlers for video tools.
    """
    tool_name = params.get("name", "")
    arguments = params.get("arguments", {})

    # ═══════════════════════════════════════════════════════════════════
    # VIDEO TOOL HANDLERS (Directive #240)
    # ═══════════════════════════════════════════════════════════════════

    if tool_name == "generate_video":
        return _handle_generate_video(arguments)

    if tool_name == "estimate_video_cost":
        return _handle_estimate_video_cost(arguments)

    if tool_name == "get_task":
        return _handle_get_task(arguments)

    # Default: forward to MCP API
    response = make_request("/tools/call", {
        "name": tool_name,
        "arguments": arguments
    })
    return response

Tool Definition Quality

A4.1/5.0
Behavior4/5

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 effectively adds valuable context beyond what the input schema provides: it discloses the cost ($0.68), mentions async tracking with a task ID, provides important usage constraints ('Send ONLY the music description'), and gives guidance on what to include in prompts. It doesn't cover rate limits or authentication needs, but provides substantial behavioral information.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded with the core purpose. Every sentence earns its place: the first states the purpose and cost, the second provides critical usage instruction, the third gives prompt guidance, and the fourth provides an example. Minor formatting issues prevent a perfect score.

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 complexity of a music generation tool with 5 parameters and no annotations or output schema, the description does a good job of providing necessary context. It covers the purpose, cost, async nature, usage constraints, and prompt guidance. The main gap is lack of information about what the tool returns (beyond mentioning a task ID) and error handling.

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 description adds some parameter semantics by providing an example prompt that illustrates the 'prompt' parameter usage and mentioning vocal style/instrumental options. However, with 100% schema description coverage, the schema already documents all 5 parameters thoroughly. The description provides marginal additional value beyond what's in the schema descriptions.

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 tool's purpose: 'Generate AI music from text description using VAP (Suno V5).' It specifies the verb ('Generate'), resource ('AI music'), and technology used ('VAP (Suno V5)'), distinguishing it from sibling tools like generate_image or generate_video.

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 provides clear context on when to use this tool by specifying it's for generating music from text descriptions and giving an example prompt. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among siblings (e.g., when to use generate_video instead).

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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