Tag-per-Track
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| API_URL | No | Endpoint of the Tag-per-Track analysis API. | https://api.tag-per-track.cloud/api/analyze |
| PRIVATE_KEY | Yes | Private key of your Base burner wallet (66 hex characters starting with 0x). Required but should be a dedicated burner wallet for security. | |
| API_BASE_URL | No | Base endpoint of the Tag-per-Track API for auxiliary routes (e.g. artist stats). | https://api.tag-per-track.cloud/api |
| MAX_SPENDING_USDC | No | Client-side spending cap per request in USDC. | 0.50 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
| prompts | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_audioA | Analyzes a music track or audio file to extract musical metadata (BPM, genre, mood, key, instruments), AI music detection verdict (HUMAN vs AI_GENERATED Suno/Udio neural vocoder risk with confidence index in 'ai_detection'), and optionally vocal lyrics. Supports local audio files via 'filePath' (read in binary and uploaded) or remote URLs via 'fileUrl'. Note: This tool automatically executes a micro-payment (0.15 USDC for standard analysis, or 0.25 USDC when extractLyrics is enabled) via the x402 protocol on Base. |
| analyze_audio_with_lyricsA | Analyzes an audio track to extract complete musical metadata, AI-generated music detection verdict (HUMAN vs AI_GENERATED Suno/Udio), AND transcribe full vocal lyrics using AI. Supports local audio files via 'filePath' (read in binary and uploaded) or remote URLs via 'fileUrl'. Note: This tool automatically executes a micro-payment of 0.25 USDC via the x402 protocol on Base. (Alias for analyze_audio with extractLyrics: true). |
| analyze_audio_batchA | Analyzes multiple music tracks or audio files in parallel (batch processing). Vastly reduces total execution time compared to sequential processing. Accepts a list of local file paths ('filePaths') or remote URLs ('fileUrls'), or a structured array of 'tracks'. Executes micro-payments per track on Base via x402. |
| lookup_artist_statsA | Retrieves streaming traction and commercial metrics for an artist (Spotify monthly listeners, followers, popularity score) for A&R qualification. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| qualify_demo_ar | Comprehensive A&R demo evaluation for record labels and music curators. Combines Essentia acoustic analysis (BPM, key, scale, moods, genres, instruments, lyrics) with real-time Spotify streaming traction (monthly listeners, popularity) to produce an A&R Executive Memo with an Emerging Gem verdict. |
| batch_demo_screening | Screens an EP, album, or folder of demo submissions in parallel using analyze_audio_batch. Evaluates energy flow, harmonic key progression, and selects standout lead singles. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
analyze_audio and analyze_audio_with_lyrics are effectively aliases since lyrics extraction can be toggled via a parameter, creating avoidable overlap. The batch and artist stats tools are clearly distinct, so the ambiguity is limited but still real.
All tool names use a consistent lowercase snake_case verb_noun structure: analyze_audio, analyze_audio_with_lyrics, analyze_audio_batch, lookup_artist_stats. The naming pattern is predictable and easy for an agent to infer.
Four tools is within a reasonable scope for an audio analysis server, but one of them is redundant with analyze_audio. Removing the alias would make the count feel tighter and more purposeful.
The core workflows are covered: single-track analysis, lyrics extraction, batch processing, and artist stats lookup. Minor gaps exist, such as analysis history or playlist-level operations, but they are not obvious dead ends for the stated domain.