Acontext
Acontext is an open-source skill memory layer for AI agents, automatically capturing and storing the learning outcomes of agents.
- Region
- Overseas
- Pricing
- Free
- Open source
- Yes
- GitHub Stars
- ★ 3.5k
- Source
- GitHub
- Added
- 2026-06-06
- Last verified
- 2026-06-06

Overview
Acontext is an open-source skill memory layer for AI agents that automatically captures and stores agent learning outcomes as readable, editable, and shareable files. It addresses the challenges of traditional agent memory being difficult to understand, debug, or inspect by users. By storing skills as Markdown files, it makes memory content transparent and easy to manage. Ideal for developers looking to improve agent learning efficiency and reusability.
Key features
- ▪Automatically captures learning outcomes
- ▪Skills stored as Markdown files
- ▪Supports cross-platform sharing and usage
- ▪No vendor lock-in risk
Use cases
Pros
- +Enhances agent learning capabilities
- +Simplifies memory management
- +Promotes knowledge reuse and sharing
Limitations / notes
- -Requires some technical background for configuration
Who it's for
This overview was compiled by AI from public sources and may contain inaccuracies — please refer to the official site.
FAQ
Which frameworks does Acontext support?
Supports any framework capable of reading files, such as LangGraph, Claude, etc.
How do I get started with Acontext?
Visit the official website to access documentation and install the required packages following the guide.
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