memodb-io/Acontext

Health v2 · maintenance only

Adoption not part of the score

3676 stars · 333 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Acontext is an open-source memory layer for AI agents that captures learnings from agent runs and stores them as human-readable Markdown skill files. It provides SDKs (Python/TypeScript), session storage, task tracking, and a learning loop so agents can reuse distilled skills across frameworks, LLMs, and runs.

Use cases

• give my ai agent persistent memory that learns from its runs
• store agent memory as readable markdown skill files instead of embeddings
• let my claude code agent improve itself over time
• capture lessons from agent sessions and reuse them next run
• share agent skills across different llm frameworks
• debug and inspect what my agent actually remembers
• self-host an agent memory service with session storage

When to choose

• you want transparent, human-editable agent memory as plain Markdown files rather than opaque embeddings
• you want agents to learn procedures and warnings from task outcomes, not just store chat facts
• you need memory portable across LangGraph, Claude, AI SDK, or any file-reading framework
• you want session storage, task tracking, and skill learning in one self-hostable service

When to avoid

• you only need semantic search over static documents - a vector store or RAG pipeline is simpler
• you need fact-based conversational memory like Mem0 or Zep rather than procedural skill learning
• you want a fully embedded library with no service dependency - Acontext runs as a platform/service

Facets

service · maturity active

agent-framework rag llm-inference sdk developer-tools self-hosted large-language-models developer-tools python self-hosted cloud agent-memory skill-files context-engineering llm-observability markdown-memory session-storage claude-code self-learning-agents ai-agents automation nodejs docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="memodb-io/Acontext")