Command Palette

Search for a command to run...

UnylyUnyly
Browse all

EzRAG Server

FreeNot checked

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

GitHubEmbed

About

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

Installing EzRAG Server

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/benbjurstrom/ezrag

FAQ

Is EzRAG Server MCP free?

Yes, EzRAG Server MCP is free — one-click install via Unyly at no cost.

Does EzRAG Server need an API key?

No, EzRAG Server runs without API keys or environment variables.

Is EzRAG Server hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install EzRAG Server in Claude Desktop, Claude Code or Cursor?

Open EzRAG Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

Related MCPs

Compare EzRAG Server with

Not sure what to pick?

Find your stack in 60 seconds

Author?

Embed badge for your README

Browse similar

All ai MCPs