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EzRAG – AI-Powered Search for Obsidian Notes

EzRAG turns your Obsidian vault into a Gemini File Search index so you can run semantic search, chat over your notes, and expose your vault through MCP tools. Everything stays in your Google account; the plugin simply keeps the index up to date.

Chat Interface Screenshot

Highlights

  • Semantic search + AI chat with inline citations
  • Smart runner pattern: one desktop keeps the index in sync, other devices can query
  • Built-in MCP server so external agents can query or fetch notes
  • Automatic deduplication, queue persistence, and rebuild workflows

Getting Started

Requirements

  • Google Gemini API key (get one free)
  • Obsidian desktop app for indexing (mobile can query/read-only)

Install

Option 1 – BRAT (recommended)

  1. Install BRAT from Community Plugins.
  2. BRAT settings → Add Beta Pluginhttps://github.com/benbjurstrom/ezrag.
  3. Enable EzRAG in Community Plugins.

Option 2 – Manual

  1. Clone into your vault:
    cd /path/to/vault/.obsidian/plugins
    git clone https://github.com/benbjurstrom/ezrag
  2. Build once:
    cd ezrag
    npm install
    npm run build
  3. Restart Obsidian and enable EzRAG.

Configure

  1. Settings → EzRAG → enter your Gemini API key.
  2. On desktop, toggle This machine is the runner to let it index.
Settings Screenshot

Using EzRAG

Chat

Open via the ribbon icon or EzRAG: Open Chat. Try prompts like:

  • “What are my notes about the Johnson project?”
  • “Summarize yesterday’s meeting notes.”
  • “Find all mentions of machine learning.”

MCP Server

Enable Settings → EzRAG → MCP Server to let tools connect.

Connect from Claude Code:

claude mcp add --transport http ezrag-obsidian-notes http://localhost:42427/mcp

Tools provided:

  • keywordSearch – keyword/regex search
  • semanticSearch – Gemini-backed semantic search with citations
  • note:///<path> – direct note retrieval

How It Works

Indexing basics

  • Only .md files are indexed; changes trigger hashing + re-upload if content changed.
  • Runner enforcement prevents multiple machines from uploading the same file.
  • Upload queue persists across restarts and surfaces status in the UI.
Upload Queue Screenshot

Limits & costs

Gemini File Search pricing (details):

  • Indexing: ~$0.15 per 1M tokens (storage free; standard model rates for queries)
  • Max file size: 100 MB; free tier ≈1 GB total storage (higher tiers up to 1 TB)
  • For best performance keep stores under ~20 GB

Data control

  • Documents live in your Google account. Manage/delete stores via Settings → Manage Stores.
  • No telemetry or note data leaves your machine beyond the Gemini File Search uploads.

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Turns your Obsidian vault into a Gemini-powered RAG index with semantic search, in-app chat, and an MCP endpoint

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