{"repo":"softmaxdata/engram","free":true,"listed":false,"github":"https://github.com/softmaxdata/engram","clone":"git clone https://github.com/softmaxdata/engram.git","description":"A brain-inspired, portable context database for AI agents","language":"Python","stars":27,"topics":["aiagent","claude","context-api","context-engineering","llm"],"license":"MIT","category":"ai-agents","readme_excerpt":"Engram A brain-inspired, portable context database for AI agents. Engram stores agent context as atomic knowledge bullets in a concept graph — not raw text. Any AI agent can connect to it regardless of which LLM or framework it uses. Context persists across sessions, transfers between models, and gets smarter with every use through reinforcement learning on context quality. Inspired by how the human brain stores and retrieves memory — associative recall, schema formation, reconsolidation, active forgetting, and consolidation — and by three lines of recent agent-memory research: Agentic Context Engineering (ACE), Dynamic Cheatsheet (DC), and Mem-α. Every other agent memory product is building a filing cabinet. Engram is building something that learns. Why bother and why Engram? Current AI agent frameworks store context as raw text, summaries, or vector chunks. This leads to: - Context decay — details lost through repeated summarization - Context isolation — Claude can't share context with GPT or Gemini - Context-as-text — no structure, no relationships, no intent tracking - No learning — context doesn't improve based on what actually worked Engram solves these with: - Agnostic and portable — We support all LLM: Claude, ChatGPT, Gemini, DeepSeek; all Agentic Frameworks: Langgraph, CrewAI, AG2; and all cloud platforms: AWS, GCP, Azure... - Atomic bullets — discrete, individually-addressable knowledge units with usage tracking - Delta operations — every mutation (including recons","default_branch":null,"files":null,"tree":[],"storefront":"/r/softmaxdata","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/softmaxdata/engram/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}