UltraContext

Hey HN! I'm Fabio and I built UltraContext, a simple context API for AI agents with automatic versioning.After two years building AI agents in production, I experienced firsthand how frustrating it is to manage context at scale. Storing messages, iterating system prompts, debugging behavior and multi-agent patterns—all while keeping track of everything without breaking anything. It was driving me insane.So I built UltraContext. The mental model is git for context:- Updates and deletes automatically create versions (history is never lost)- Replay state at any pointThe API is 5 methods: uc.create() // new context (can fork from existing) uc.append() // add message uc.get() // retrieve by version, timestamp, or index uc.update() // edit message → creates version uc.delete() // remove message → creates version Messages are schema-free. Store conversation history, tool calls, system prompts—whatever shape you need. Pass it straight to your LLM using any framework you'd like.What it's for:- Persisting conversation state across sessions- Debugging agent behavior (rewind to decision point)- Forking contexts to test different flows- Audit trails without building audit infrastructure- Multi-agent and sub-agent patternsWhat it's NOT:- Not a memory/RAG system (no semantic search)- Not a vector database- Not an Orchestration/LLM frameworkUltraContext handles versioning, branching, history. You get time-travel with one line.Docs: https://ultracontext.ai/docsEarly access: https://ultracontext.aiWould love feedback! Especially from anyone who's rolled their own context engineering and can tell me what I'm missing.