Found 17 results for sparc
Production-ready AI agent orchestration platform with 66 specialized agents, 213 MCP tools, ReasoningBank learning memory, and autonomous multi-agent swarms. Built by @ruvnet with Claude Agent SDK, neural networks, memory persistence, GitHub integration,
Comprehensive development framework with SPARC methodology for AI-assisted software development, multi-platform publishing (WordPress, PayloadCMS, Astro, Docusaurus, Mintlify), and Coolify deployment
SPARC 2.0 - Autonomous Vector Coding Agent + MCP. SPARC 2.0, vectorized AI code analysis, is an intelligent coding agent framework built to automate and streamline software development. It combines secure execution environments, and version control into a
Transform README files into GitHub project plans with AI-powered agent teams
NPX package to scaffold new projects with SPARC methodology structure
This module provides bindings for the Capstone disassembly framework.
Intelligent project generator with 54+ boilerplate templates, AI agent orchestration, and complete application building using SPARC methodology
Claude Collab - The AI collaboration framework that prevents echo chambers
🧠Gemini Flow - AI-Powered Development Orchestration with Google Gemini API Integration
Enhanced Development System for Claude - Combines SPARC methodology with iterative planning
The AI collaboration framework that prevents echo chambers - Real-time collaboration with diversity enforcement
AI-powered development orchestration for Gemini CLI - adapted from Claude Code Flow by ruvnet
Claude-Flow with enhanced TaskMaster integration - AI, Enterprise & Autonomous features
AI-driven CI/CD pipeline automation for GitHub projects using Claude-Flow and SPARC methodology
Advanced AI agent orchestration system for Claude Code with AWS Bedrock integration, SPARC methodology, and multi-agent swarm coordination
AI-driven CI/CD pipeline automation for GitHub projects using Claude-Flow and SPARC methodology
AI-driven CI/CD pipeline automation for GitHub projects using Claude-Flow and SPARC methodology