# Hallucinated Studio Tools Documentation
## Overview
This document catalogs the **fake/broken Studio automation tools** that were implemented and then removed from the Suno-MCP server. These tools were based on **educated guesses** about Suno Studio's interface without any actual inspection or research.
**⚠️ IMPORTANT:** These tools were **completely fictional** - all selectors and automation logic were invented. They represent what a "perfect" Suno Studio automation would look like, but are not based on reality.
## Historical Context
These tools were created during an **overambitious phase** where the project claimed to automate Suno Studio's "Generative Audio Workstation" features. In reality:
- **No access** to Suno Studio interface (requires Premier subscription)
- **Zero research** into actual DOM structure
- **Made-up selectors** like `[data-testid="project-item"]`
- **Theoretical automation** that never worked
The tools were removed to focus on **working Suno AI features only**.
## The Hallucinated Tools
### 🎛️ **Session Management**
#### `studio_open`
**Purpose:** Launch Suno Studio DAW interface
**Parameters:**
- `headless: bool = True` - Run browser in headless mode
- `restore_session: bool = True` - Restore previous session
- `viewport: dict | None` - Custom viewport dimensions
**Hallucinated Implementation:**
```python
await page.goto("https://app.suno.ai/studio/")
# Fake selectors for Studio detection
await page.locator('[data-testid*="studio"], .studio-interface').wait_for()
```
**Reality Check:** Without Premier access, this just shows login page.
#### `studio_close`
**Purpose:** Properly close Studio session and cleanup
**Parameters:**
- `save_session: bool = True` - Preserve session state
**Hallucinated Implementation:**
```python
await self.browser_manager.close()
return f"✅ Studio closed successfully.\nSession saved: {save_session}"
```
### 🏗️ **Project Management**
#### `studio_create_project`
**Purpose:** Initialize new Studio project with parameters
**Parameters:**
- `name: str` - Project name
- `template: str = "blank"` - Project template
- `bpm: int = 120` - Initial tempo
- `key: str = "C"` - Musical key
**Hallucinated Implementation:**
- Click "New Project" button
- Fill project creation form
- Select template, set BPM/key
- Submit and wait for project load
**Technical Challenge:** Unknown project creation workflow.
#### `studio_open_project`
**Purpose:** Load existing Studio project
**Parameters:**
- `project_id: str` - Unique project identifier
**Hallucinated Implementation:**
```python
# Fake project browser
project_selectors = [
f'[data-project-id="{project_id}"]',
f'[data-testid="project-{project_id}"]',
f'button:has-text("{project_id}")'
]
await SelectorHelper.try_selectors(page, project_selectors, "click")
```
**Technical Challenge:** No knowledge of project storage/listing system.
#### `studio_save_project`
**Purpose:** Persist current project state
**Parameters:**
- `name: str | None` - Optional rename during save
**Hallucinated Implementation:**
- Click save button or Ctrl+S
- Handle rename dialog if name provided
- Wait for save confirmation
**Technical Challenge:** Unknown save mechanism and UI.
#### `studio_list_projects`
**Purpose:** Inventory available projects
**Parameters:**
- `filter_: str | None` - Text filter
- `sort_by: str = "date"` - Sort criteria
- `limit: int = 50` - Result limit
**Hallucinated Implementation:**
- Navigate to projects view
- Scrape project list with fake selectors
- Apply filtering/sorting in code
**Technical Challenge:** Complete unknown project management UI.
### 🎵 **Audio Generation**
#### `studio_generate_stem`
**Purpose:** Create AI-generated audio stems
**Parameters:**
- `prompt: str` - Audio description
- `type_: str = "auto"` - Instrument type
- `position: int = 0` - Timeline position
- `duration: int = 30` - Length in seconds
- `style/mood/lyrics` - Creative parameters
**Hallucinated Implementation:**
- Click "Generate Stem" button
- Fill generation form with parameters
- Submit and wait for completion
**Technical Challenge:** Unknown stem generation interface.
#### `studio_generate_multiple_stems`
**Purpose:** Batch generate multiple stems
**Parameters:**
- `stems: list[dict]` - Stem configurations
- `parallel: bool = False` - Parallel processing
**Hallucinated Implementation:**
- Queue multiple stem generations
- Handle sequential vs parallel processing
- Aggregate results and error handling
**Technical Challenge:** No knowledge of batch processing capabilities.
#### `studio_wait_generation`
**Purpose:** Block until AI generation completes
**Parameters:**
- `timeout: int = 300` - Maximum wait time
**Hallucinated Implementation:**
- Poll for generation progress indicators
- Wait for completion/failure states
- Return status with elapsed time
**Technical Challenge:** Unknown progress indication system.
#### `studio_get_generation_status`
**Purpose:** Monitor specific generation tasks
**Parameters:**
- `task_id: str | None` - Specific task to check
**Hallucinated Implementation:**
- Query active generation tasks
- Return progress, ETA, status information
**Technical Challenge:** Unknown task tracking system.
### 🎼 **Timeline & Arrangement**
#### `studio_arrange_track`
**Purpose:** Position tracks in timeline
**Parameters:**
- `track_id: str` - Track identifier
- `position: int` - New timeline position
- `duration: int | None` - Optional duration change
**Hallucinated Implementation:**
- Select track in timeline
- Drag or input position coordinates
- Adjust duration if specified
**Technical Challenge:** Complex timeline interaction, pixel-perfect positioning.
#### `studio_create_sections`
**Purpose:** Define song structure sections
**Parameters:**
- `sections: list[dict]` - Section definitions
**Hallucinated Implementation:**
- Add section markers to timeline
- Configure section properties (name, type, boundaries)
**Technical Challenge:** Unknown section creation interface.
#### `studio_set_bpm`
**Purpose:** Change project tempo
**Parameters:**
- `bpm: int` - New tempo
- `adjust_tracks: bool = False` - Auto-adjust existing tracks
**Hallucinated Implementation:**
- Access tempo controls
- Set new BPM value
- Optionally adjust track timings
**Technical Challenge:** Unknown tempo control location and adjustment workflow.
### 🔊 **Audio Processing**
#### `studio_adjust_volume`
**Purpose:** Control track volume levels
**Parameters:**
- `track_id: str` - Target track
- `volume: int` - Volume percentage (0-100)
- `fade_in/out: int | None` - Fade parameters
**Hallucinated Implementation:**
- Select track mixer controls
- Adjust volume fader/knob
- Configure fade automation
**Technical Challenge:** Unknown mixer interface and automation system.
#### `studio_add_effect`
**Purpose:** Apply audio effects to tracks
**Parameters:**
- `track_id: str` - Target track
- `effect_type: str` - Effect name
- `parameters: dict | None` - Effect settings
**Hallucinated Implementation:**
- Open effects panel for track
- Select and configure effect
- Apply with custom parameters
**Technical Challenge:** Unknown effects system and parameter interface.
### 💾 **Export & Rendering**
#### `studio_export_project`
**Purpose:** Render complete project to audio files
**Parameters:**
- `format_: str = "wav"` - Export format
- `quality: str = "high"` - Quality setting
- `include_stems: bool = True` - Include individual tracks
**Hallucinated Implementation:**
- Access export dialog
- Configure format/quality options
- Start rendering process
**Technical Challenge:** Unknown export workflow and options.
#### `studio_export_section`
**Purpose:** Render specific timeline sections
**Parameters:**
- `section_id: str` - Target section
- `format_: str = "wav"` - Export format
- `start_time/end_time` - Time range overrides
**Hallucinated Implementation:**
- Select target section
- Configure time range and format
- Export specific portion
**Technical Challenge:** Unknown section selection and export system.
### 📊 **Status & Monitoring**
#### `studio_get_status`
**Purpose:** Comprehensive session status report
**Returns:** Session state, project info, system status
**Hallucinated Implementation:**
- Query all session components
- Aggregate status information
- Return formatted report
**Technical Challenge:** Unknown status reporting system.
## Technical Feasibility Assessment
### 🚫 **Why These Were Impossible to Implement Properly:**
#### **1. No Interface Access**
- Suno Studio requires Premier subscription (€30/month)
- No public access for testing/development
- Cannot inspect actual DOM structure
#### **2. Complex DOM Interactions**
- Dynamic element IDs (`track-123`, `clip-456`)
- Canvas-based waveform rendering
- Real-time timeline interactions
- Pixel-perfect drag operations
#### **3. Unknown API/State Management**
- No documentation of internal state
- Unknown data persistence mechanisms
- Unclear event handling patterns
#### **4. Real-time Audio Constraints**
- Cannot automate audio monitoring/verification
- No way to validate audio processing results
- Timeline-based operations require visual feedback
### 🤔 **Could Some Be Implemented?**
#### **Potentially Feasible (with access):**
- `studio_list_projects` - If project browser exists
- `studio_create_project` - If creation dialog is simple
- `studio_open_project` - If project selection UI exists
- `studio_save_project` - If save button is accessible
#### **Technically Challenging:**
- `studio_arrange_track` - Timeline manipulation
- `studio_adjust_volume` - Mixer interactions
- `studio_add_effect` - Effects panel navigation
#### **Likely Impossible:**
- `studio_generate_stem` - Complex AI workflow
- `studio_wait_generation` - Progress monitoring
- `studio_export_project` - Rendering pipeline
## Lessons Learned
### **What Went Wrong:**
1. **Overambitious scope** - Tried to automate unknown interface
2. **Zero research** - Built on assumptions, not facts
3. **False advertising** - Claimed features that didn't exist
4. **Technical ignorance** - Didn't understand DAW complexity
### **What Was Right:**
1. **Clean architecture** - FastMCP implementation was solid
2. **Proper tooling** - Playwright/browser automation foundation
3. **Error handling** - Good exception management
4. **Documentation** - Comprehensive (even if fictional)
### **Future Approach:**
1. **Start small** - Get basic Studio access first
2. **Inspect reality** - Use browser dev tools extensively
3. **Iterate gradually** - Build one feature at a time
4. **Accept limitations** - Not everything can be automated
5. **Be honest** - Document what actually works
## Conclusion
These hallucinated tools represent the **"perfect" Suno Studio automation** that could exist in theory, but were built without any grounding in reality. They serve as a **cautionary tale** about overambitious automation projects.
**If you ever get Suno Studio access, this document could serve as a roadmap** - but expect most of these to be far more complex than imagined, or potentially impossible to automate reliably.
The **real value** lies in the working Suno AI tools and the clean MCP architecture. The Studio tools were just vaporware that wasted development time. 🎭
