Acontext
Memory layer that stores agent experience as reusable skills.
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Use cases
About Acontext
Acontext is listed in our memory & RAG category and is aimed at builders. Memory layer that stores agent experience as reusable skills. Pricing, as the maker states it: Open source. Maturity: Active. We last checked the official link on 2026-10-16.
What is Acontext?
Acontext is an open-source skill memory layer for AI agents. It automatically captures learnings from agent runs and stores them as agent skill files you can read, edit and share across agents, LLMs and frameworks.
The aim is for agents to learn from mistakes and reuse what worked without opaque memory polluting the context.
Sources: the official README and our directory listing, checked 2026-10-18. Official site: acontext.io.
Who is Acontext for?
Developers who want agent learnings stored as readable, shareable skills.
Acontext at a glance
- Open source: Yes (Apache License 2.0)
- GitHub: memodb-io/Acontext · 3,696 stars (as of Oct 21, 2026)
Key features
- Captures learnings automatically
- Stores them as skill files
- Shareable across agents and frameworks
Acontext FAQ
What is Acontext?
Acontext is an open-source skill memory layer for AI agents. It automatically captures learnings from agent runs and stores them as agent skill files you can read, edit and share across agents, LLMs and frameworks.
Who is Acontext for?
Developers who want agent learnings stored as readable, shareable skills.
Is Acontext free?
Acontext's pricing, as the maker states it: Open source. Open-source tools are free to use, though you may still pay for model API usage or a hosted plan. Check the official site for current plans.
Is Acontext open source?
Yes. Acontext is released under the Apache License 2.0, according to its GitHub repository.
What are alternatives to Acontext?
Similar tools include Hindsight, AgentMemory, EverOS, Pieces, SimpleMem and projectmem.
Acontext ratings and reviews
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Acontext alternatives
Other memory & RAG tools in our directory. See all memory & RAG tools →
Hindsight
Agent memory system that stores experiences and learns from them so agents improve over time.
AgentMemory
Persistent memory layer for AI coding agents.
EverOS
Local-first, portable memory layer for AI agents stored as Markdown.
Pieces
AI memory layer that captures context from your work so you and your AI tools can recover decisions and resume where you left off.
SimpleMem
Research-backed lifelong memory library for LLM agents that stores, compresses and retrieves text and multimodal memories, usable over MCP.
projectmem
A local-first memory layer for coding agents that records issues, attempts, fixes and decisions and warns your agent before it repeats a past mistake.
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