Muninn – The universal memory layer for AI agents

Summary: Muninn indexes projects into local Markdown files to provide precise, token-efficient context retrieval for AI agents like Claude and Cursor. It operates locally with a Rust-powered engine, reducing token usage by up to 95% and improving AI memory management.

What it does

Muninn scans your filesystem to create transparent Markdown indexes of your knowledge, enabling selective injection of relevant information into AI context windows. It supports multiple AI tools through a universal memory layer.

Who it's for

It is designed for users who need persistent, efficient context management across AI agents with limited memory capacity.

Why it matters

Muninn addresses the "goldfish memory" problem by avoiding costly, full-file context dumps and enabling fast, precise retrieval of relevant data for AI workflows.