kahz12

kahz12 / Grimore-MD

Public

Local-first cognitive daemon for automated vault management Markdown. Semantic indexing, auto-tagging, and connection discovery using LLMs and vector search.

30
3
100% credibility
Found May 01, 2026 at 30 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Grimoire automatically organizes Markdown notes by adding tags, summaries, and connections using local AI, enabling natural-language queries over a personal knowledge vault.

How It Works

1
📖 Discover Grimoire

You hear about Grimoire, a friendly helper that organizes your personal notes into a smart, connected web of ideas.

2
🛠️ Set it up quickly

You download it to your computer and get everything ready in just a few simple steps, no hassle.

3
📁 Point to your notes

You show it the folder where you keep all your everyday notes, like a digital journal or idea vault.

4
🧠 Wake the smart helper

You connect a thinking brain that runs right on your computer to understand and tag your notes automatically.

5
🔍 Run the first scan

You press scan, and it reads every note, adds helpful tags, short summaries, and suggests links between related ideas.

6
Ask your own questions

You chat with it by asking things like 'What connects my thoughts on this topic?' and get clear answers with links to your notes.

Your knowledge glows

Now your notes feel alive, automatically updating and revealing hidden connections whenever you add more.

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Star Growth

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AI-Generated Review

What is Grimore-MD?

Grimore-MD is a Python-based, local-first daemon that automates Markdown vault management by watching your notes folder, applying semantic indexing with LLMs and vector search, auto-tagging content, and discovering connections between ideas. It solves the chaos of growing personal knowledge bases—like Obsidian or Logseq vaults—by turning raw notes into a queryable cognitive engine, all without sending data off your machine via Ollama. Run CLI commands like `grimoire scan` for initial indexing, `daemon start` for real-time updates, or `ask` for RAG-powered answers with citations.

Why is it gaining traction?

Its local-first design stands out—no API keys, no cloud dependency—making it a privacy win over hosted tools like Reflect or Mem. The daemon auto-tags and injects wikilinks on file changes with Git safety nets and dry-run previews, while hybrid search fuses exact keyword matches with fuzzy semantics for reliable discovery. Developers dig the idempotent scans that skip unchanged notes and the reversible outputs via pre-commit snapshots.

Who should use this?

PKM power users with Markdown vaults who want automated tagging and connection discovery without SaaS lock-in. Obsidian/Logseq note-takers drowning in untagged files, or researchers querying local notes on topics like "Heidegger's nihilism." Solo devs building offline knowledge graphs for code docs or project retrospectives.

Verdict

Worth a spin for local-first Markdown automation if you run Ollama—solid CLI, config, and safety features punch above its 30 stars and 1.0% credibility score. Still early (light tests, v2.0), so test on a Git-backed vault first; roadmap promises contradictions detection and multi-format ingest.

(198 words)

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