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UltraContext

A simple context API for AI agents with auto-versioning

Details

External ID
46706442
Source
HN
Company
—
Product
UltraContext
Website domain
ultracontext.ai
Launched
Jan. 21, 2026
Cohort
—
Upvotes
21
Upvotes percentile
0.6587615283267457
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

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.

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
context management api for ai agents
Manually corrected
False

Could you build this?

Yes It is a CRUD and session-management API with a CLI and local daemon that syncs agent context to a server and provides versioning and search.

Discussion

20 comments analyzed.

Competitors mentioned: memtree.dev (message compression API), Portkey (LLM middleware), Vector databases (Pinecone, Weaviate), Claude Code's built-in sub-agents

Concerns raised: Privacy/trust of storing messages on servers, Latency overhead from API call between agent and LLM, Scaling with very large datasets (10k+ messages), Version history explosion with frequent agent runs, Reinventing wheel vs using vector databases

Feature requests: Open-source the product, Client-side encryption or local-first deployment, Compression strategies for long-running agents, Parallel request option without middleware interception

Competitors

Other products that read as similar to this one — 309 launches clear the similarity bar, closest 8 shown.

Attention rank: #111 of 310 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 84 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.