MCP server for generating game background music using DeepSeek for scene analysis and Soundraw for music generation
Server has 4 well-structured tools with complete JSON Schema definitions and reasonable descriptions. All tools follow verb_noun naming (generate_bgm, get_bgm_variations, adaptive_layer_control, scene_transition_music). Schemas include proper type constraints, enums, and parameter descriptions. However, descriptions are generic and lack LLM-optimized guidance on WHEN to use each tool vs. alternatives. Output schemas are not documented, LLMs cannot predict response structure. Error handling is minimal (generic try/catch). No tool annotations (destructiveHint, idempotentHint). Parameter descriptions lack actionable constraints (e.g., 'duration_seconds' says '10-300' but doesn't explain why or when to pick values in that range).
Generate multiple versions of a track with different stems muted for adaptive game audio. Creates separate audio files for each layer configuration that can be mixed in real-time based on gameplay.
Generate background music for a game scene. Uses DeepSeek to analyze the scene and map to Soundraw parameters, then generates music via Soundraw API. Returns audio URL, share link, and optional game engine integration code.
Generate a variation of an existing BGM using Soundraw. Use "similar" to create a new song with similar style, or "customize" to adjust energy levels or mute stems of the original.
Generate transition music between two game scenes. Uses DeepSeek to analyze the emotional journey between scenes and creates appropriate transition audio with dynamic energy levels.
Output schemas not documented. LLMs cannot predict response structure (audio URL, share link, integration code fields). Forces agents to guess field names and types.
Tool descriptions lack LLM-optimized guidance. Missing WHEN to use each tool vs. alternatives. E.g., when should agent call get_bgm_variations vs. generate_bgm? When is adaptive_layer_control needed?
No tool annotations (destructiveHint, idempotentHint). All 4 tools call external APIs and generate/modify music, agents need to know these are write operations with side effects.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 64 | <=2025-11-25 | v2 |
Parameter descriptions lack actionable constraints. E.g., 'duration_seconds' (10-300) doesn't explain why those bounds exist or how to choose. 'mood' is optional but no guidance on when it's needed.
Error handling is generic (try/catch returns JSON error). No recovery guidance. If Soundraw API fails, agent doesn't know if it's retryable, rate-limited, or auth failure.