Suno-MCP
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- FlicenseBqualityDmaintenanceEnables AI music generation through Suno, allowing users to create songs with custom lyrics or AI-generated content, wait for completion, and download MP3 files.7-
- FlicenseNot gradedqualityCmaintenanceEnables AI music generation and management through the Suno API, supporting text prompts, custom lyrics, track status monitoring, and credit management.14-
- AlicenseAqualityDmaintenanceEnables AI-powered music generation through natural language commands, supporting both inspiration mode (AI-generated lyrics and style) and custom mode (user-provided lyrics and parameters) to create songs with direct download links.43MIT
- AlicenseNot gradedqualityDmaintenanceEnables semantic search of local audio samples by describing sounds, MIDI generation, stem separation, and other music production tools from Claude Desktop.2MIT
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TDQS
Scored across 10 tools
Every tool has a clearly distinct purpose with no ambiguity. Each tool targets a specific action on a specific resource (e.g., generate_track vs. download_track vs. track_info), and even similar-sounding tools like track_extend and track_remix have clearly differentiated functions described in their arguments.
All tools follow a consistent suno_verb_noun pattern throughout (e.g., suno_generate_track, suno_download_track, suno_track_info). The naming is predictable and readable, with no deviations in convention or style.
With 10 tools, this is well-scoped for automating Suno AI interactions. Each tool earns its place, covering browser management, authentication, track generation, library access, and track operations, without being overly sparse or bloated.
The tool surface is nearly complete for the Suno AI domain, covering login, browser setup, track generation, extension, remixing, info retrieval, library listing, and downloading. A minor gap is the lack of a tool to delete or manage tracks beyond generation, but core workflows are well-covered.