IWE - Memory system for you and your AI Agents

Your second brain that AI agents can navigate. A structured knowledge graph for humans and machines.

Knowledge Graph

A messy knowledge base provides messy context to an AI, and messy context yields poor results.

The knowledge you need keeps growing. Codebases expand. Documentation multiplies. Decisions pile up. It's hard to keep it all in your head—or fit it in a context window.

We've all been there: you capture an insight, file it away, and two weeks later it's gone—buried in folders or scattered across apps. When you ask AI for help, you're feeding it fragments hoping something sticks. IWE gives both you and your AI the same map to navigate—one source of truth, shared understanding.

IWE is a knowledge graph that organizes your notes hierarchically and makes them accessible to AI agents. Write in Markdown, structure with links, give AI agents the tools to navigate your knowledge.

IWE has no built-in AI — it's designed to work with external AI tools (like Claude, Codex, Gemini, and others). The CLI provides structured access to your knowledge graph, whether you're scripting your own workflows or giving AI agents the tools and context they need.

Why IWE?

Local-first — your data stays on your machine as directory with Markdown files
Hierarchical knowledge graph — same note in multiple contexts without duplication using inclusion links
External memory for AI — CLI tools let AI agents retrieve and update your knowledge with full context
Editor integration — search, navigate, refactor notes via LSP (VS Code, Neovim, Zed, Helix)
Blazing fast — Rust-powered, processes thousands of notes instantly

The Hierarchical Knowledge Graph

IWE organizes your notes as a hierarchical knowledge graph — notes with links and nesting:

Hierarchy — inclusion links create parent-child relationships, organizing notes into a tree
Cross-links — reference links connect notes across the hierarchy
Polyhierarchy — the same note can appear under multiple parents without duplication
Context inheritance — enrich any note with details from all its parents

This structure makes retrieval powerful: ask for a topic and get its full context—children, parents, and related notes—in a single query.

Editor Integration (LSP)

IWE integrates with VS Code, Neovim, Zed, Helix, and other editors via the Language Server Protocol (LSP). Get IDE-like features for your markdown: search, auto-complete, go to definition, find references, rename refactoring, and more.

IWE understands document structure—headers, lists, and links—and provides advanced refactorings like extract/inline notes via code actions. It supports standard Markdown, wiki-style links, tables, and other extensions.

Search — find notes by title or content
Navigate — go to definition, find references (backlinks)
Preview — hover over links to see content
Auto-complete — link suggestions as you type
Inlay hints — show parent references and link counts
Extract — pull sections into new notes
Inline — embed note content back into parent
Rename — rename files with automatic link updates
Format — normalize documents, update link titles
Transform — pipe text through external commands
Templates — create notes from templates (daily notes, etc.)
Outline conversion — switch between headers and lists

More information: LSP Features

Working with AI (CLI)

IWE provides CLI tools for AI agents to read, navigate, and modify your knowledge graph:

Read

find — search documents with fuzzy matching and relationship filters
retrieve — fetch documents with depth and context expansion
tree — display hierarchical structure from any starting point
squash — consolidate multiple documents into a single context

Write

new — create documents from templates, accepts content via stdin
extract — extract sections into new documents
inline — embed referenced content back into parent document
rename — rename documents with automatic link updates
delete — remove documents and clean up references

Example: retrieve a topic with 2 levels of children and 1 level of parent context:

iwe retrieve -k topic -d 2 -c 1

Unlike vector databases where agent memory becomes opaque—embeddings you can't read or edit—IWE keeps everything in plain Markdown. No similarity thresholds, no "maybe relevant" results. The agent gets exactly the documents that connect to the topic.

You remain in control. The files are yours, readable and editable. Agents become collaborators that can navigate your knowledge, not black boxes that store it.

More information:

Quick Start

Install the CLI and LSP server:

Using Homebrew (macOS/Linux):
```
brew tap iwe-org/iwe
brew install iwe
```
Or using Cargo:
```
cargo install iwe iwes
```
Initialize your workspace:
```
cd ~/notes
iwe init
```
Configure your editor — VS Code · Neovim · Helix · Zed
Teach your AI agent — ask it to learn the iwe command using its built-in help

Documentation

Getting Started — Installation and setup
Usage Guide — Editor features and workflows
CLI Reference — Command-line tools
Working with AI — AI agent integration
Configuration — Settings and customization

Get Involved

IWE is open source and community-driven. Join the discussions, report issues, or contribute to the documentation.

Editor plugins: VS Code · Neovim · Zed

License

Apache License 2.0

Iwe

Install / Use

README