NeuroStack

A local RAG layer and optimizer for the Markdown knowledge base you already have.

NeuroStack indexes a folder of .md files (Obsidian, Logseq, Notion exports, plain Markdown) into SQLite with FTS5, embeddings and a wiki-link graph, and exposes it to any MCP client as search, RAG answers with citations, graph queries and agent memories. It then keeps the base accurate: it flags notes that have gone stale, harvests decisions and root causes from AI sessions into memories, synthesises recurring memories into learnings, and queues proven ones for promotion into notes. Indexing never modifies your files. Optional MCP write tools let a client author or edit notes through your git history.

npm install -g neurostack && neurostack init

Works with Claude, Cursor, Windsurf, Gemini CLI, VS Code, Codex and any other client that supports MCP.

Your notes, in your control

By default, NeuroStack is a read-only indexing layer:

• Indexing, search, summaries, and graph analysis never modify your Markdown files
• All index data lives in NeuroStack's own separate database
• To remove it completely, run neurostack uninstall. Your notes stay untouched.
• Nothing ever leaves your machine, unless you configure a third-party LLM provider for summaries and embeddings

If your vault is a git repo, four opt-in MCP write tools let an AI client author and edit notes for you: vault_write_file, vault_delete_file, plus vault_read_file / vault_list_files. Every write commits and pushes to your git remote with a descriptive message, so every change is visible in git log, revertable with git revert, and serialised under a per-vault lock. Writes hard-reject invalid frontmatter, paths outside the vault, and hidden directories (.git, .obsidian, …). Because the tools are exposed to any client talking to neurostack serve, gate them at the transport (auth, tunnel, LAN only) if you put the MCP endpoint on the public internet.

Who this is for

You do not need to be a developer. If you take notes in Markdown, or can export your notes as Markdown from Obsidian, Notion, Bear, or Roam, NeuroStack works for you.

Get started in three steps

You will need Node.js installed (most computers already have it). The npm package handles the Python setup for you.

Step 1. Install

npm install -g neurostack

Step 2. Set up (takes about two minutes)

neurostack init

The setup wizard asks which vault folder to index, which mode to run (Lite or Full), and which profession pack to apply. It does everything else automatically.

Step 3. Connect to your AI

For Claude Desktop:

neurostack setup-desktop

For Claude Code:

claude mcp add neurostack -- neurostack serve

For Cursor, Windsurf, Gemini CLI, or VS Code:

neurostack setup-client cursor      # or: windsurf, gemini, vscode

Done. Open a new conversation and ask your AI about something from your notes.

neurostack init --mode lite ~/my-notes    # lite mode
neurostack init --mode full ~/my-notes    # full mode

# PyPI
pipx install neurostack
pip install neurostack        # inside a venv
uv tool install neurostack

# One-line script
curl -fsSL https://raw.githubusercontent.com/raphasouthall/neurostack/main/install.sh | bash

# Lite mode (no ML deps)
curl -fsSL https://raw.githubusercontent.com/raphasouthall/neurostack/main/install.sh | NEUROSTACK_MODE=lite bash

What it does

• Hybrid search (FTS5 keyword + semantic) with tiered depth, so a client can fetch triples, summaries or full notes by token budget.
• RAG answers with inline [[citations]] over the CLI, MCP, or an OpenAI-compatible API.
• Stale detection. A note that keeps surfacing in contexts where it no longer fits is flagged and demoted in later results.
• Session harvest. A timer scans Claude Code, Codex, Gemini and omp transcripts and saves decisions, bugs, conventions and learnings as memories with TTLs.
• Synthesis and promotion. Recurring memories become learnings; a promotion queue lists which ones are ready to become notes.
• Wiki-link graph with PageRank, community detection, gap and bridge analysis.
• Read-only by default. Opt-in write tools commit and push every change to your git remote.

What makes it different

NeuroStack is not a replacement for Obsidian, Notion, or any note-taking app. It sits on top of what you already use and adds what they don't have.

Stale detection is the part other tools lack. When a note keeps appearing in contexts where it no longer fits, such as a deprecated API or a superseded paper, NeuroStack flags it and demotes it in later results.

Profession packs

When you run neurostack init, you choose a profession pack. Each one configures NeuroStack with templates, folder structures, and AI guidance suited to how your profession actually uses notes.

Apply a pack to an existing vault without losing any notes:

neurostack scaffold researcher ~/my-notes    # or: writer, student, developer, devops, data-scientist

You can also import an existing Markdown directory:

neurostack onboard ~/my-notes

How retrieval works

Most memory tools give your AI a wall of text and let it figure out what's relevant. NeuroStack is tiered. It starts with the cheapest retrieval that answers the question and escalates only when it needs to.

Simple factual questions resolve at ~15 tokens. Deep dives get full context. Your AI spends its attention budget where it matters.

Your AI remembers decisions