A comprehensive, curated collection of AI tools, frameworks, and resources for developers building intelligent applications.
View Documentation • Getting Started • Quick Reference
AI Universe provides a carefully curated collection of 110+ open-source AI tools and frameworks, organized into 16 comprehensive categories. Each entry has been verified for active maintenance, production readiness, and includes real performance metrics.
- Foundation Models - Latest LLMs, vision models, and multimodal systems
- Infrastructure - Training, inference, and optimization frameworks
- Developer Tools - AI coding assistants and IDEs
- Skills & Extensions - Plugins for AI assistants
- MCP Servers - Model Context Protocol servers
- Vector Databases - Embedding storage and semantic search
- Observability - LLM monitoring and debugging tools
- RAG & Knowledge - Retrieval and knowledge management
- Production AI - MLOps, deployment, and serving platforms
- AI Safety - Security, guardrails, and ethical AI
# Clone the repository
git clone https://github.com/KomalSrinivasan/ai-universe.git
cd ai-universe
# Install dependencies
pip install -r requirements.txt
# Run locally
mkdocs serveVisit http://localhost:8000 to view the documentation.
The full documentation is available at komalsrinivasan.github.io/ai-universe and includes:
- Getting Started Guide - Introduction to AI development and tool selection
- Quick Reference - Find tools by use case and requirements
- Best Practices - Production-ready patterns and recommendations
- Category Deep Dives - Detailed analysis of tools in each category
Contributions are welcome. Please ensure submissions meet these criteria:
- Open source with clear licensing
- Active maintenance (commits within 6 months)
- Production-ready or significant research value
- Documented installation and usage
See CONTRIBUTING.md for detailed guidelines.
ai-universe/
├── docs/
│ ├── index.md # Homepage
│ ├── categories/ # Category pages (16 total)
│ ├── guides/ # Getting started, reference, best practices
│ └── stylesheets/ # Custom styling
├── scripts/
│ └── release.sh # Semantic versioning script
├── mkdocs.yml # MkDocs configuration
└── requirements.txt # Python dependencies
This project uses semantic versioning. To create a new release:
./scripts/release.sh [patch|minor|major]This will update the version, create a git tag, and trigger automated deployment.
- SkillsMP.com - 66,500+ AI agent skills
- MCP.so - 20,100+ Model Context Protocol servers
- Hugging Face - 230K+ datasets, models, and spaces
MIT License - see LICENSE for details.
Komal Vardhan Lolugu Lead Product Engineer - Agentic AI & Generative Models
For questions or collaboration opportunities, please reach out via LinkedIn.