Build an innovative Model Context Protocol (MCP) implementation for Masa's Subnet 42. Think of MCP as a USB-C port for AI applications - it standardizes how AI models connect to and utilize different data sources and contextual information.
- 🥇 1st place: $2,500
- 🥈 2nd place: $1,250
- 🥉 3rd place: $750
- 4th place: $300
- 5th place: $200
- Design and implement a Model Context Protocol
- Create interfaces for data source integration
- Develop context management systems
- Bonus: Integration with Bittensor ecosystem
- Novel approaches to context handling
- Creative data integration methods
- Unique applications of contextual awareness
- Efficient resource utilization
- Low latency responses
- Scalable architecture
- Clear implementation guide
- Protocol specification
- Integration examples
.
├── src/ # Your implementation
├── docs/ # Your documentation
│ ├── IMPLEMENTATION.md
│ └── SPECIFICATION.md
├── tests/ # Your tests
└── README.md
- Fork this repository
- Build your MCP implementation
- Document your approach
- Submit via pull request
MCP ensures models evolve beyond static training data by:
- Providing standardized access to contextual data
- Enabling real-time data integration
- Supporting dynamic context management
- Facilitating transparent decision processes
Masa Subnet 42 is a decentralized data layer for AI agents and applications, featuring:
- Real-time data pipelines
- Decentralized storage solutions
- Enterprise time series capabilities
- Vector store functionality
Submissions will be judged on:
- Protocol design elegance
- Implementation quality
- Performance metrics
- Documentation clarity
- Integration ease
- Clone this repository
- Review the challenge requirements
- Design your solution
- Implement and test
- Submit your work
This project is licensed under the MIT License - see the LICENSE file for details.