This toolkit provides a structured approach to software development using the SPARC methodology, AI-driven code generation (AIGI), and AI assistance via Roo Code and Model Context Protocol (MCP). It targets developers seeking to enhance efficiency, modularity, and security in their projects by integrating AI agents with external services.

How It Works

The project leverages the SPARC methodology (Specification, Pseudocode, Architecture, Refinement, Completion), breaking down development into distinct AI-assisted phases. It integrates with the Roo Code VS Code extension, enabling specialized AI agents for each phase. MCP facilitates secure connections to external services like databases and APIs, allowing AI agents to interact with real-world systems.

Quick Start & Requirements

• Install via npx create-sparc init or npx create-sparc aigi init for AIGI projects.
• Requires VS Code with the Roo Code extension installed.
• Official documentation: https://github.com/ruvnet/rUv-dev (Note: The README links to the GitHub repo for documentation, not a dedicated docs site).

Highlighted Details

• Implements SPARC methodology for structured, modular, and secure development.
• MCP integration allows AI agents to securely interact with external services (Supabase, OpenAI, GitHub, AWS, Firebase).
• Offers specialized modes for various development tasks: Orchestrator, Specification Writer, Architect, Auto-Coder, Tester, Debugger, Security Reviewer, Documentation Writer, System Integrator, Deployment Monitor, Optimizer, DevOps, and more.
• Supports TypeScript projects with configurable templates and symlink support.

Maintenance & Community

• Created by Reuven Cohen.
• Contributions are welcome via GitHub pull requests.
• For questions or support, open an issue on the GitHub repository.

Licensing & Compatibility

• MIT License.
• Permissive license suitable for commercial use and closed-source linking.

Limitations & Caveats

The project is described as a toolkit and framework, implying it requires integration and configuration within a VS Code environment with the Roo Code extension. Specific AI model compatibility or performance benchmarks are not detailed in the README.