Markdown

MarkMem is a git-native, plain-markdown memory layer for chatbots that stores every fact as an inspectable Markdown file in a git repository, backed by a rebuildable SQLite cache. It combines bi-temporal facts in YAML, a Presidio PII write gate, and git as the compliance surface, so you can cat, grep, and git-diff your chatbot’s memory instead of trusting an opaque vector database. What is MarkMem and why do chatbots forget? Every chatbot that carries context across sessions faces the same problem: the model’s context window is finite, and once a conversation scrolls past it, the details are gone. Traditional memory layers solve this by embedding facts into a vector database and retrieving the most similar chunks at query time. That works, but it turns your chatbot’s memory into a black box — you cannot read it, audit it, or prove what it contains. ...

AgentBrain is a local-first, long-term memory tool for AI agents that stores everything as a plain Markdown vault. Instead of locking your agent’s memory into a proprietary database or cloud API, it gives you an append-only Markdown folder you can read, edit, grep, and version with Git. It uses index-first retrieval with CJK-aware BM25 to stay token-efficient, and enforces human-approved consolidation to prevent multi-agent write conflicts. What Is AgentBrain? A Local-First Markdown Memory Vault for AI Agents AgentBrain is an open-source Python tool (Python 3.10+) that gives AI agents a durable, local-first memory layer stored as plain Markdown files. The core idea is simple: an agent’s long-term knowledge should live in a human-readable folder on your own machine, not inside a black-box database or a third-party cloud service. ...