# Product Requirements Document (PRD)
## Suno MCP Server: AI Music Generation Automation Platform
**Version:** 1.0
**Date:** January 27, 2025
**Author:** Sandra Schipal
**Status:** Active Development
---
## Executive Summary
The Suno MCP Server is an advanced browser automation platform that enables seamless integration between Claude Desktop and **Suno's revolutionary AI DAW** - Suno Studio. This product provides automated access to Suno Studio's back-and-forth music generation capabilities, enabling users to leverage the full power of conversational AI music creation through Claude Desktop.
### Key Value Propositions
- **Suno Studio Integration**: Automated access to Suno's AI DAW with back-and-forth generation
- **Conversational Music Creation**: Enable iterative, conversational music production workflows
- **Professional Workflow Integration**: Seamlessly integrate AI music generation into existing production pipelines
- **Scalable Automation**: Support batch processing and complex multi-track projects
- **Future-Proof Architecture**: Built to adapt to evolving AI music platforms and features
---
## Product Vision
### Mission Statement
To provide powerful automation tools that enable seamless integration between Claude Desktop and Suno's revolutionary AI DAW, empowering users to leverage the full capabilities of conversational music creation through automated workflows.
### Vision Statement
Become the leading automation platform for Suno Studio, enabling users to harness the power of AI-powered music production through Claude Desktop integration.
### Success Metrics
- **User Adoption**: 1,000+ active users within 6 months
- **Generation Volume**: 10,000+ tracks generated monthly
- **User Satisfaction**: 4.5+ star rating in community reviews
- **Platform Reliability**: 99.5% uptime for automation services
- **Feature Utilization**: 80%+ users utilizing Studio features
---
## Market Analysis
### Target Market
- **Primary**: Content creators, podcasters, video producers
- **Secondary**: Independent musicians, hobbyists, music educators
- **Tertiary**: Professional music producers, game developers, filmmakers
### Market Size
- **Total Addressable Market (TAM)**: $2.1B (AI music generation market)
- **Serviceable Addressable Market (SAM)**: $500M (browser automation segment)
- **Serviceable Obtainable Market (SOM)**: $50M (MCP automation tools)
### Competitive Landscape
- **Direct Competitors**: None (first-to-market MCP automation for Suno)
- **Indirect Competitors**: Manual Suno usage, other AI music platforms
- **Competitive Advantages**:
- First MCP integration for Suno
- Comprehensive Studio beta support
- Professional-grade automation features
- Open-source, extensible architecture
### Market Timing Advantage
Suno is currently in aggressive growth mode:
- **Estimated Team**: ~20 developers
- **Infrastructure**: ~200 LLM instances running 24/7
- **Pricing Strategy**: 50% discounts to build user base
- **Cost Structure**: Likely operating at loss per generation
- **Opportunity**: Get in before pricing optimization
---
## User Personas
### Persona 1: Content Creator "Sarah"
- **Demographics**: 28, video content creator, 50K subscribers
- **Pain Points**: Needs background music for videos, limited music budget
- **Goals**: Create unique, royalty-free music quickly
- **Use Cases**: Generate intro/outro music, background tracks for videos
### Persona 2: Independent Musician "Marcus"
- **Demographics**: 35, bedroom producer, aspiring artist
- **Pain Points**: Limited production skills, expensive studio time
- **Goals**: Create demos and finished tracks efficiently
- **Use Cases**: Generate stems, experiment with styles, create backing tracks
### Persona 3: Game Developer "Alex"
- **Demographics**: 32, indie game developer, small team
- **Pain Points**: Limited audio budget, needs diverse music styles
- **Goals**: Create game soundtracks and ambient music
- **Use Cases**: Generate level music, ambient tracks, character themes
---
## Product Requirements
### Functional Requirements
#### Core Platform Features
1. **Browser Automation Engine**
- Support for Chrome, Firefox, Safari, Edge
- Headless and GUI operation modes
- Session persistence and recovery
- Cross-platform compatibility (Windows, Mac, Linux)
2. **Suno AI Integration**
- Automated login and authentication
- Track generation from text prompts
- Style and mood specification
- Lyrics integration support
- Download management and organization
3. **Suno Studio Beta Support**
- Project creation and management
- AI stem generation (vocals, drums, bass, synths)
- Multitrack timeline manipulation
- Professional mixing and effects
- Advanced export capabilities
4. **MCP Protocol Compliance**
- Full Model Context Protocol support
- Claude Desktop integration
- Tool-based architecture
- Error handling and recovery
#### Advanced Features
1. **Batch Processing**
- Multiple track generation
- Queue management system
- Parallel processing capabilities
- Progress monitoring and reporting
2. **Project Management**
- Project templates and presets
- Version control and history
- Collaboration features
- Export and sharing options
3. **Quality Control**
- Automated quality assessment
- Generation retry logic
- Error detection and recovery
- Performance optimization
### Non-Functional Requirements
#### Performance
- **Response Time**: < 2 seconds for tool execution
- **Generation Time**: < 5 minutes for standard tracks
- **Throughput**: Support 100+ concurrent users
- **Resource Usage**: < 500MB RAM per active session
#### Reliability
- **Uptime**: 99.5% availability
- **Error Rate**: < 1% failure rate
- **Recovery Time**: < 30 seconds for service restoration
- **Data Integrity**: 100% data consistency
#### Security
- **Authentication**: Secure credential handling
- **Data Protection**: No credential storage or logging
- **Privacy**: User data isolation
- **Compliance**: GDPR and CCPA compliance
#### Scalability
- **Horizontal Scaling**: Support multiple server instances
- **Load Balancing**: Distribute user load efficiently
- **Resource Management**: Dynamic resource allocation
- **Monitoring**: Real-time performance tracking
---
## Technical Architecture
### System Architecture
```
┌─────────────────────────────────────────────────────────────┐
│ Suno MCP Server │
├─────────────────────────────────────────────────────────────┤
│ MCP Protocol Layer │
│ ├── Tool Definitions │
│ ├── Request Handling │
│ ├── Response Formatting │
│ └── Error Management │
├─────────────────────────────────────────────────────────────┤
│ Automation Engine │
│ ├── Browser Management │
│ ├── Session Controller │
│ ├── Workflow Engine │
│ └── State Management │
├─────────────────────────────────────────────────────────────┤
│ Platform Integrations │
│ ├── Suno AI Interface │
│ ├── Suno Studio Interface │
│ ├── File Management │
│ └── Export Engine │
├─────────────────────────────────────────────────────────────┤
│ Data Layer │
│ ├── Configuration Store │
│ ├── Session Persistence │
│ ├── Project Database │
│ └── Logging System │
└─────────────────────────────────────────────────────────────┘
```
### User Journey Flow
```
User Request → Claude Desktop → MCP Protocol → Suno MCP Server
↓
Browser Automation
↓
Suno AI/Studio
↓
Music Generation
↓
File Download
↓
Response to User
```
### Technology Stack
- **Runtime**: Node.js 18+
- **Automation**: Playwright 1.40+
- **Protocol**: Model Context Protocol SDK
- **Validation**: Zod schema validation
- **Testing**: Jest + Playwright Test
- **Documentation**: Markdown + JSDoc
### Integration Points
- **Claude Desktop**: MCP protocol communication
- **Suno AI Platform**: Browser automation interface
- **Suno Studio**: Advanced DAW automation
- **File System**: Local file management
- **Cloud Storage**: Optional cloud integration
---
## Feature Specifications
### Phase 1: Foundation (Weeks 1-2)
**Goal**: Establish core automation capabilities
#### Features
- Basic browser automation setup
- Suno AI login and authentication
- Simple track generation
- File download management
- Error handling framework
#### Acceptance Criteria
- [ ] Successfully automate Suno AI login
- [ ] Generate tracks from text prompts
- [ ] Download completed tracks
- [ ] Handle common error scenarios
- [ ] Maintain session state
#### Success Metrics
- 95% successful login rate
- 90% successful track generation
- < 5 second average tool response time
### Phase 2: Core Features (Weeks 3-4)
**Goal**: Implement essential Studio features
#### Features
- Suno Studio project management
- AI stem generation
- Generation monitoring
- Enhanced error recovery
- Session persistence
#### Acceptance Criteria
- [ ] Create and manage Studio projects
- [ ] Generate individual stems (vocals, drums, bass)
- [ ] Monitor generation progress
- [ ] Recover from failed generations
- [ ] Persist sessions across restarts
#### Success Metrics
- 85% successful stem generation
- 90% generation completion rate
- < 3 minute average stem generation time
### Phase 3: Advanced Features (Weeks 5-6)
**Goal**: Professional production capabilities
#### Features
- Timeline manipulation
- Track arrangement
- BPM and tempo control
- Section management
- Advanced mixing tools
#### Acceptance Criteria
- [ ] Arrange tracks on timeline
- [ ] Set and adjust project BPM
- [ ] Create song sections
- [ ] Apply volume and panning
- [ ] Add audio effects
#### Success Metrics
- 80% successful arrangement operations
- 95% BPM adjustment accuracy
- < 2 second timeline operation response
### Phase 4: Professional Tools (Weeks 7-8)
**Goal**: Production-quality features
#### Features
- Advanced effects processing
- Automation capabilities
- Real-time monitoring
- Professional mixing
- Quality control systems
#### Acceptance Criteria
- [ ] Apply professional audio effects
- [ ] Create automation curves
- [ ] Monitor real-time performance
- [ ] Implement mixing workflows
- [ ] Quality assessment algorithms
#### Success Metrics
- 90% effect application success
- 95% automation accuracy
- < 1 second monitoring response time
### Phase 5: Export & Integration (Weeks 9-10)
**Goal**: Complete production workflow
#### Features
- Advanced export options
- Stem separation
- MIDI export
- Cloud integration
- Batch processing
#### Acceptance Criteria
- [ ] Export multiple audio formats
- [ ] Separate individual stems
- [ ] Export MIDI data
- [ ] Integrate with cloud storage
- [ ] Process multiple projects
#### Success Metrics
- 95% successful export rate
- 100% format compatibility
- < 30 second export time
### Phase 6: Testing & Optimization (Weeks 11-12)
**Goal**: Production-ready release
#### Features
- Comprehensive testing suite
- Performance optimization
- Error handling improvements
- Documentation completion
- User acceptance testing
#### Acceptance Criteria
- [ ] 90%+ test coverage
- [ ] Performance benchmarks met
- [ ] Error handling validated
- [ ] Documentation complete
- [ ] User feedback incorporated
#### Success Metrics
- 95% test pass rate
- All performance targets met
- < 0.5% error rate
- 4.5+ user satisfaction rating
---
## User Experience Design
### User Journey Map
#### Discovery Phase
1. **Awareness**: User learns about Suno MCP through documentation
2. **Interest**: User explores features and capabilities
3. **Evaluation**: User reviews examples and use cases
4. **Decision**: User decides to implement the solution
#### Onboarding Phase
1. **Installation**: User installs dependencies and configures MCP
2. **Configuration**: User sets up Claude Desktop integration
3. **First Use**: User runs initial automation commands
4. **Learning**: User explores advanced features
#### Usage Phase
1. **Daily Use**: User incorporates automation into workflow
2. **Feature Adoption**: User discovers and uses advanced features
3. **Optimization**: User refines workflows and processes
4. **Scaling**: User expands usage to more complex projects
#### Retention Phase
1. **Satisfaction**: User achieves desired outcomes
2. **Advocacy**: User recommends solution to others
3. **Feedback**: User provides improvement suggestions
4. **Evolution**: User adapts to new features and updates
### Interface Design Principles
- **Simplicity**: Clear, intuitive command structure
- **Consistency**: Uniform parameter naming and behavior
- **Feedback**: Comprehensive status and progress reporting
- **Error Recovery**: Graceful handling of failures
- **Documentation**: Extensive examples and guides
---
## Risk Analysis
### Technical Risks
#### High Risk
- **Platform Changes**: Suno UI modifications breaking automation
- *Mitigation*: Robust selector strategies, regular testing
- *Impact*: High - could break core functionality
- *Probability*: Medium
- **Rate Limiting**: Suno API restrictions affecting automation
- *Mitigation*: Implement backoff strategies, queue management
- *Impact*: High - could limit generation capacity
- *Probability*: Medium
#### Medium Risk
- **Browser Compatibility**: Cross-browser automation issues
- *Mitigation*: Comprehensive testing, fallback strategies
- *Impact*: Medium - affects user experience
- *Probability*: Low
- **Performance Degradation**: Slow automation affecting user experience
- *Mitigation*: Performance monitoring, optimization
- *Impact*: Medium - affects user satisfaction
- *Probability*: Low
#### Low Risk
- **Dependency Updates**: Breaking changes in dependencies
- *Mitigation*: Version pinning, regular updates
- *Impact*: Low - manageable with updates
- *Probability*: Low
### Business Risks
#### High Risk
- **Competition**: Similar solutions entering market
- *Mitigation*: Rapid feature development, community building
- *Impact*: High - could reduce market share
- *Probability*: Medium
- **Platform Dependency**: Over-reliance on Suno platform
- *Mitigation*: Multi-platform support, abstraction layers
- *Impact*: High - could limit growth
- *Probability*: Low
#### Medium Risk
- **User Adoption**: Slow adoption of automation features
- *Mitigation*: Better documentation, examples, tutorials
- *Impact*: Medium - affects growth trajectory
- *Probability*: Medium
- **Legal Issues**: Terms of service violations
- *Mitigation*: Compliance review, legal consultation
- *Impact*: Medium - could affect operations
- *Probability*: Low
---
## Success Criteria
### Launch Criteria
- [ ] All Phase 1-3 features implemented and tested
- [ ] 90%+ test coverage achieved
- [ ] Performance benchmarks met
- [ ] Documentation complete
- [ ] User acceptance testing passed
### Growth Criteria
- [ ] 100+ active users within 1 month
- [ ] 1,000+ tracks generated monthly
- [ ] 4.0+ user satisfaction rating
- [ ] 95%+ automation success rate
- [ ] Community contributions received
### Long-term Success Criteria
- [ ] 1,000+ active users within 6 months
- [ ] 10,000+ tracks generated monthly
- [ ] 4.5+ user satisfaction rating
- [ ] 99.5%+ platform uptime
- [ ] Multiple platform integrations
---
## Implementation Timeline
### Development Phases
#### Phase 1: Foundation (Weeks 1-2)
- **Week 1**: Browser automation setup, basic Suno integration
- **Week 2**: Login automation, track generation, error handling
#### Phase 2: Core Features (Weeks 3-4)
- **Week 3**: Studio project management, stem generation
- **Week 4**: Generation monitoring, session persistence
#### Phase 3: Advanced Features (Weeks 5-6)
- **Week 5**: Timeline manipulation, track arrangement
- **Week 6**: BPM control, section management
#### Phase 4: Professional Tools (Weeks 7-8)
- **Week 7**: Effects processing, automation
- **Week 8**: Real-time monitoring, mixing tools
#### Phase 5: Export & Integration (Weeks 9-10)
- **Week 9**: Advanced export, stem separation
- **Week 10**: MIDI export, cloud integration
#### Phase 6: Testing & Optimization (Weeks 11-12)
- **Week 11**: Comprehensive testing, performance optimization
- **Week 12**: Documentation, user acceptance testing
### Milestones
- **M1 (Week 2)**: Basic automation functional
- **M2 (Week 4)**: Studio features operational
- **M3 (Week 6)**: Advanced features complete
- **M4 (Week 8)**: Professional tools ready
- **M5 (Week 10)**: Full workflow complete
- **M6 (Week 12)**: Production-ready release
---
## Resource Requirements
### Development Team
- **Lead Developer**: Full-time, 12 weeks
- **QA Engineer**: Part-time, 8 weeks
- **Technical Writer**: Part-time, 4 weeks
- **DevOps Engineer**: Part-time, 2 weeks
### Infrastructure
- **Development Environment**: Cloud-based development servers
- **Testing Infrastructure**: Automated testing pipeline
- **Documentation Platform**: Markdown-based documentation system
- **Version Control**: Git-based repository management
### Budget Estimate
- **Development**: $50,000 (team costs)
- **Infrastructure**: $5,000 (cloud services, tools)
- **Testing**: $3,000 (testing tools, services)
- **Documentation**: $2,000 (tools, platforms)
- **Suno Subscriptions**: $4,800 (20 Premier accounts × $20/month × 12 months)
- **Total**: $64,800
### Operational Cost Analysis
**Suno Premier Subscription Costs:**
- **Current Pricing**: ~$20/month (50% discount)
- **Full Price**: ~$40/month
- **Per Automation Instance**: $0.10/hour (assuming 200 hours/month usage)
- **20 Dev Environment**: $400/month total
- **Annual Cost**: $4,800
**Cost Per Generated Track:**
- **Average Generation Time**: 3 minutes
- **Cost Per Track**: ~$0.005 (at $20/month subscription)
- **Break-even**: ~4,000 tracks/month per subscription
- **ROI**: Positive after 2,000 tracks per subscription
---
## Conclusion
The Suno MCP Server represents a significant opportunity to democratize music creation through AI automation. By providing seamless integration between Claude Desktop and Suno's powerful music generation platforms, this product addresses a real market need while positioning itself as a first-mover in the AI music automation space.
The comprehensive feature set, robust technical architecture, and phased implementation approach ensure a high probability of success. With proper execution, this product can become the standard for AI music automation, enabling creators of all skill levels to produce professional-quality music efficiently.
The success of this product will be measured not just by technical metrics, but by its impact on the creative community - empowering more people to express themselves through music and reducing the barriers to professional music production.
---
**Document Control**
- **Version**: 1.0
- **Last Updated**: January 27, 2025
- **Next Review**: February 10, 2025
- **Approved By**: Sandra Schipal
- **Distribution**: Development Team, Stakeholders
