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EzRAG Server

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Provides semantic search and keyword search over Obsidian notes, along with direct note retrieval, allowing external AI agents to query and access the vault.

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Описание

Provides semantic search and keyword search over Obsidian notes, along with direct note retrieval, allowing external AI agents to query and access the vault.

README

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.

Links

from github.com/benbjurstrom/ezrag

Установка EzRAG Server

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/benbjurstrom/ezrag

FAQ

EzRAG Server MCP бесплатный?

Да, EzRAG Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для EzRAG Server?

Нет, EzRAG Server работает без API-ключей и переменных окружения.

EzRAG Server — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить EzRAG Server в Claude Desktop, Claude Code или Cursor?

Открой EzRAG Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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