The AI coding assistant revolution is here, but there's a critical missing piece: context. Today's AI assistants are powerful, but they lack persistent memory, organized knowledge bases, and the ability to coordinate across multiple sessions.
AI-native code editor that auto-builds with advanced semiconductor smarts—powered by your knowledge and MCP superpowers.
Developed by FutureAtoms, ChipOS represents a fundamental shift in how we think about AI-powered development. It's not just another code editor or AI assistant—it's the command center that gives your AI tools the context, memory, and coordination capabilities they need to be truly effective.
The Context Problem
Modern AI coding assistants like Claude Code, Cursor, and Windsurf are incredibly capable, but they all face the same challenge: they start fresh every time. Your carefully crafted documentation, your project-specific conventions, your accumulated knowledge—all of it must be re-explained in every conversation.
This creates several critical bottlenecks. Teams spend countless hours repeatedly explaining the same concepts to their AI assistants. Important context gets lost between sessions. And coordinating multiple AI agents on complex tasks becomes nearly impossible without a shared knowledge base.
How ChipOS Works
At its core, ChipOS is a Model Context Protocol server—a standardized way for AI assistants to access external knowledge and capabilities. But it's what ChipOS does with that protocol that makes it revolutionary.
Intelligent Knowledge Management
ChipOS allows you to build and maintain a comprehensive knowledge base for your projects. Crawl websites for API documentation. Upload PDFs of technical specifications. Organize code examples and best practices. ChipOS ingests it all and makes it instantly accessible to your AI assistants.
But this isn't just a document storage system. ChipOS uses advanced retrieval-augmented generation (RAG) strategies to ensure your AI assistants get exactly the right context for each query. The system understands relationships between documents, tracks which information is most relevant for different types of tasks, and continuously learns from how you and your AI assistants interact with the knowledge base.
ChipOS Core Capabilities
- Website crawling for API documentation and technical resources
- PDF and document upload with intelligent indexing
- Repository ingestion for code-aware search
- Hybrid RAG (BM25 + vector) with reranking
- Knowledge Inspector for chunk visibility
- Integration with Claude Code, Cursor, Windsurf, and more
- Projects, tasks, and Agent Work Orders
Seamless AI Integration
ChipOS implements the Model Context Protocol, which means it works seamlessly with any MCP-compatible AI coding assistant. Connect Claude Code for sophisticated reasoning, Cursor for rapid development, or Windsurf for collaborative coding—they all get instant access to your shared knowledge base.
The beauty of this approach is that your AI assistants can now build on each other's work. One assistant can document a complex system, another can write tests based on that documentation, and a third can refine the implementation—all working from the same shared understanding.
Task Management That Actually Helps
Beyond knowledge management, ChipOS provides integrated task tracking designed specifically for AI-assisted development. Create tasks, assign them to different AI assistants, and watch as ChipOS coordinates their efforts using your shared knowledge base.
The system understands task dependencies, can suggest next steps based on completed work, and ensures that all AI assistants working on your project have the context they need to be effective. It's project management that finally understands how AI-powered development actually works.
Built for the Real World
ChipOS was designed from the ground up to be practical and production-ready. The system runs entirely on your infrastructure or hosted mode—Docker containers for easy deployment, managed Postgres for robust data storage, and support for multiple AI providers including OpenAI, Anthropic, Google, OpenRouter, Grok, and Ollama.
The architecture is straightforward: a React frontend for managing your knowledge base and tasks, a Python FastAPI backend for the MCP server, and clean APIs that make integration simple. Everything is designed to be maintainable, scalable, and easy to customize for your specific needs.
Real-World Impact
Development teams using ChipOS report transformative changes in how they work with AI assistants. One startup with just three engineers was able to accomplish what would typically require a team of ten by leveraging ChipOS to coordinate multiple AI assistants, each with full access to the project's knowledge base.
Enterprise teams are using ChipOS to standardize how their developers interact with AI tools. Instead of each developer maintaining their own prompts and context, the entire team works from a shared, continuously updated knowledge base that captures best practices and institutional knowledge.
The Future of AI-Powered Development
ChipOS represents just the beginning of what's possible when we properly contextualize AI coding assistants. The roadmap includes enhanced code understanding capabilities, deeper integration with development tools, and advanced multi-agent orchestration features.
But the core vision remains the same: give AI coding assistants the context they need to be truly effective partners in software development. With ChipOS, we're not just making AI assistants more capable—we're fundamentally changing how development teams work.
Getting Started
ChipOS is available now for macOS and Linux. The system is open-source and designed to be easy to deploy—get started in minutes with Docker Compose or use the hosted dashboard, configure your knowledge sources, and connect your AI coding assistants.
Whether you're a solo developer looking to supercharge your AI workflow or an enterprise team standardizing AI-assisted development, ChipOS provides the foundation for more effective, context-aware AI coding assistance.