Acontext
Acontext is an open-source memory layer for AI agents that automatically captures learnings from agent runs and stores them as plain Markdown skill files. Agents can read, edit, and share these skills across different LLMs and frameworks without vendor lock-in or semantic embeddings.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | memodb-io/Acontext |
| Owner | memodb-io |
| Primary language | JavaScript |
| License | Apache-2.0 — OSI-approved |
| Stars | 3.6k |
| Forks | 323 |
| Open issues | 35 |
| Latest release | sdk-ts/v0.1.21 (2026-04-08) |
| Last updated | 2026-06-30 |
| Source | https://github.com/memodb-io/Acontext |
What Acontext is
Acontext provides a skill memory system where agent learnings are distilled via LLM and stored as structured Markdown files organized by a schema you define. Agents retrieve skills via tool calls (get_skill, get_skill_file) rather than semantic search, enabling progressive disclosure and local file-based portability across frameworks.
Get the Acontext source
Clone the repository and explore it locally.
git clone https://github.com/memodb-io/Acontext.gitcd Acontext# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Define your SKILL.md schema upfront to specify the structure and naming of skill files. The system routes and updates skills based on this schema, so clear governance prevents skill fragmentation.
- Integrate Skill Content Tools (get_skill, get_skill_file) into your agent's tool set. The agent must be able to call these tools to retrieve and reason about skills during execution.
- Distillation is triggered on task completion or failure. Implement explicit outcome reporting in your agent logic or rely on automatic detection. Monitor learning latency; production agents do not block on learning.
- Plan for skill versioning and conflict resolution. Acontext stores skills as files; use Git or a version control strategy to manage iterations across teams and agent versions.
- Test skill portability early. Export a ZIP of learned skills and verify they work with target frameworks (LangGraph, Claude, etc.) to catch schema or tool incompatibilities.
When to avoid it — and what to weigh
- High-frequency semantic retrieval needs — Acontext uses tool-based retrieval (agent reasoning) rather than embedding-based similarity search. If you need sub-millisecond top-k similarity queries at scale, vector databases are better suited.
- Real-time knowledge graph requirements — Acontext optimizes for skill file simplicity and portability, not graph traversal or complex relational queries. If your use case requires ACID transactions or deep relationship queries, consider a graph or relational database.
- Heavily regulated compliance with immutable audit trails — While skill files are versionable via Git, Acontext's architecture and security posture for compliance-grade audit logging are not clearly documented. Requires review before deployment in HIPAA, SOC2, or similar environments.
- Extremely resource-constrained environments — Self-hosting requires Docker and an LLM API (default gpt-4.1). Cloud mode depends on Acontext's hosted infrastructure. Not suitable for highly resource-limited edge devices or air-gapped systems without careful planning.
License & commercial use
Apache License 2.0 (Apache-2.0) — a permissive OSI-approved license. Allows commercial use, modification, and distribution with minimal restrictions. Requires attribution and includes warranty disclaimers.
Apache-2.0 is a permissive license that explicitly permits commercial use. You may use Acontext in commercial products without license fees. However, the LICENSE file and any modifications must include proper attribution. Review the full Apache 2.0 license terms and consult legal counsel if compliance auditing is required for your use case.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Good |
| Assessment confidence | Medium |
Not clearly stated. Considerations to investigate: (1) API key storage and rotation for self-hosted instances; (2) encryption of skill files in transit and at rest; (3) authentication and authorization between agents and the Acontext backend; (4) data retention and deletion policies; (5) LLM API key handling during distillation. Self-hosting requires running local Docker containers; audit your network and image security accordingly. Cloud mode depends on Acontext's server-side security posture—requires review of their privacy policy and compliance certifications.
Alternatives to consider
LangChain Memory / LangGraph State
Built-in memory primitives for LangChain/LangGraph agents. Tightly coupled to framework; less portable and harder to inspect than plain skill files. No auto-distillation.
Pinecone / Weaviate vector databases
Semantic retrieval at scale via embeddings. Fast similarity search; opaque vector representations. Requires embedding re-training for portability. Better for high-throughput retrieval, worse for transparency.
Firebase / Firestore
Managed NoSQL with real-time sync and offline support. No built-in agent learning or skill distillation. Generic database; requires custom logic to implement memory layer and schema governance.
Build on Acontext with DEV.co software developers
Start with Acontext cloud (free credits at acontext.io) or self-host locally. Explore docs and join the Discord community to learn how to integrate skill memory into your agent workflow.
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Acontext FAQ
Can I use Acontext with frameworks other than LangGraph or Claude?
What happens to my skills if I leave Acontext?
Does Acontext use embeddings for memory?
Can I self-host Acontext?
Work with a software development agency
Need help beyond evaluating Acontext? DEV.co is a software development agency offering software development services and web development for teams of every size. Our software developers and web developers build custom software, web applications, APIs, and ai frameworks integrations — and maintain them long-term.
Ready to build transparent, learning agents?
Start with Acontext cloud (free credits at acontext.io) or self-host locally. Explore docs and join the Discord community to learn how to integrate skill memory into your agent workflow.