rm-mcp 0.1.0

MCP server for accessing reMarkable tablet data

reMarkable MCP Server

Unlock the full potential of your reMarkable tablet as a second brain for AI assistants. This MCP server lets Claude, VS Code Copilot, and other AI tools read, search, and traverse your entire reMarkable library — including handwritten notes via OCR.

Why rm-mcp?

Your reMarkable tablet is a powerful tool for thinking, note-taking, and research. But that knowledge stays trapped on the device. This MCP server changes that:

• Full library access — Browse folders, search documents, read any file
• Typed text extraction — Native support for Type Folio and typed annotations
• Handwriting OCR — Convert handwritten notes to searchable text
• PDF & EPUB support — Extract text from documents, plus your annotations
• Smart search — Find content across your entire library
• Second brain integration — Use with Obsidian, note-taking apps, or any AI workflow

Whether you're researching, writing, or developing ideas, rm-mcp lets you leverage everything on your reMarkable through AI.

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Quick Install

☁️ Cloud Mode

Uses the reMarkable Cloud API. Requires a reMarkable Connect subscription.

1. Get a One-Time Code

Go to my.remarkable.com/device/browser/connect and generate a code.

2. Convert to Token

uvx rm-mcp --register YOUR_CODE

3. Install

Or configure manually in .vscode/mcp.json:

{
  "inputs": [
    {
      "type": "promptString",
      "id": "remarkable-token",
      "description": "reMarkable API Token",
      "password": true
    },
    {
      "type": "promptString",
      "id": "google-vision-key",
      "description": "Google Vision API Key",
      "password": true
    }
  ],
  "servers": {
    "remarkable": {
      "command": "uvx",
      "args": ["rm-mcp"],
      "env": {
        "REMARKABLE_TOKEN": "${input:remarkable-token}",
        "GOOGLE_VISION_API_KEY": "${input:google-vision-key}"
      }
    }
  }
}

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Tools

Tool	Description
remarkable_read	Read and extract text from documents (with pagination and search)
remarkable_browse	Navigate folders or search by document name
remarkable_search	Search content across multiple documents
remarkable_recent	Get recently modified documents
remarkable_status	Check connection status
remarkable_image	Get PNG/SVG images of pages (supports OCR via sampling)

All tools are read-only and return structured JSON with hints for next actions.

📖 Full Tools Documentation

Smart Features

• Auto-redirect — Browsing a document path returns its content automatically
• Auto-OCR — Notebooks with no typed text automatically enable OCR
• Batch search — Search across multiple documents in one call
• Vision support — Get page images for visual context (diagrams, mockups, sketches)
• Sampling OCR — Use client's AI for OCR on images (no API key needed)

Example Usage

# Read a document
remarkable_read("Meeting Notes")

# Search for keywords
remarkable_read("Project Plan", grep="deadline")

# Enable OCR for handwritten notes
remarkable_read("Journal", include_ocr=True)

# Browse your library
remarkable_browse("/Work/Projects")

# Search across documents
remarkable_search("meeting", grep="action items")

# Get recent documents
remarkable_recent(limit=10)

# Get a page image (for visual content like UI mockups or diagrams)
remarkable_image("UI Mockup", page=1)

# Get SVG for editing in design tools
remarkable_image("Wireframe", output_format="svg")

# Get image with OCR text extraction (uses sampling if configured)
remarkable_image("Handwritten Notes", include_ocr=True)

# Transparent background for compositing
remarkable_image("Logo Sketch", background="#00000000")

# Compatibility mode: return resource URI instead of embedded resource
remarkable_image("Diagram", compatibility=True)

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Resources

Documents are automatically registered as MCP resources:

URI Scheme	Description
remarkable:///{path}.txt	Extracted text content
remarkableimg:///{path}.page-{N}.png	PNG image of page N (notebooks only)
remarkablesvg:///{path}.page-{N}.svg	SVG vector image of page N (notebooks only)

📖 Full Resources Documentation

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OCR for Handwriting

For handwritten content, rm-mcp offers several OCR backends. Choose based on your setup and requirements:

Backend	Setup	Quality	Offline	Best For
Sampling	No API key	Depends on client model	✅	Users with capable AI clients
Google Vision	API key	Excellent	❌	Best handwriting accuracy
Tesseract	System install	Poor for handwriting	✅	Printed text, offline fallback

Quick Setup

Set REMARKABLE_OCR_BACKEND in your MCP config:

{
  "env": {
    "REMARKABLE_OCR_BACKEND": "sampling"
  }
}

Options: sampling, google, tesseract, auto

📖 Sampling OCR (No API Key)

Uses your MCP client's AI model for OCR. Works with clients that support MCP sampling (VS Code + Copilot, Claude Desktop, etc.).

Pros:

• No additional API keys needed
• Quality depends on your client's model (GPT-4, Claude, etc.)
• Private — handwriting stays local to your client

Cons:

• Only available with sampling-capable clients
• Falls back to Google Vision (if API key configured) or Tesseract if sampling unavailable

📖 Google Cloud Vision

Provides consistently excellent handwriting recognition.

Setup:

1. Enable Cloud Vision API
2. Create an API key
3. Add to config: "GOOGLE_VISION_API_KEY": "your-key"

Cost: 1,000 free requests/month, then ~$1.50 per 1,000.

📖 Full Google Vision Setup Guide

📖 Tesseract (Fallback)

Open-source OCR designed for printed text. Poor results with handwriting, but useful as an offline fallback.

# Install Tesseract
# macOS
brew install tesseract

# Ubuntu/Debian
sudo apt install tesseract-ocr

# Windows
choco install tesseract

Default Behavior (auto)

When REMARKABLE_OCR_BACKEND=auto (default):

1. Google Vision (if GOOGLE_VISION_API_KEY is set)
2. Tesseract (fallback)

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Advanced Configuration

Root Path Filtering

Limit the MCP server to a specific folder on your reMarkable. All operations will be scoped to this folder:

{
  "servers": {
    "remarkable": {
      "command": "uvx",
      "args": ["rm-mcp"],
      "env": {
        "REMARKABLE_TOKEN": "your-token",
        "REMARKABLE_ROOT_PATH": "/Work",
        "GOOGLE_VISION_API_KEY": "your-api-key"
      }
    }
  }
}

With this configuration:

• remarkable_browse("/") shows contents of /Work
• remarkable_browse("/Projects") shows /Work/Projects
• Documents outside /Work are not accessible

Useful for:

• Focusing on work documents during office hours
• Separating personal and professional notes
• Limiting scope for specific AI workflows

Custom Background Color

Set the default background color for image rendering:

{
  "servers": {
    "remarkable": {
      "command": "uvx",
      "args": ["rm-mcp"],
      "env": {
        "REMARKABLE_TOKEN": "your-token",
        "REMARKABLE_BACKGROUND_COLOR": "#FFFFFF"
      }
    }
  }
}

Supported formats:

• #RRGGBB — RGB hex (e.g., #FFFFFF for white)
• #RRGGBBAA — RGBA hex (e.g., #00000000 for transparent)

Default is #FBFBFB (reMarkable paper color). This affects both the remarkable_image tool and image resources.

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Use Cases

Research & Writing

Use rm-mcp while working in an Obsidian vault or similar to transfer knowledge from your handwritten notes into structured documents. AI can read your research notes and help develop your ideas.

Daily Review

Ask your AI assistant to summarize your recent notes, find action items, or identify patterns across your journal entries.

Document Search

Find that half-remembered note by searching across your entire library — including handwritten content.

Knowledge Management

Treat your reMarkable as a second brain that AI can access. Combined with tools like Obsidian, you can build a powerful personal knowledge system.

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Documentation

Guide	Description
Google Vision Setup	Set up handwriting OCR
Tools Reference	Detailed tool documentation
Resources Reference	MCP resources documentation
Capability Negotiation	MCP protocol capabilities
Development	Contributing and development setup
Future Plans	Roadmap and planned features

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Development

git clone https://github.com/wavyrai/rm-mcp.git
cd rm-mcp
uv sync --all-extras
uv run pytest test_server.py -v

📖 Development Guide

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License

MIT

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Built with rmscene, PyMuPDF, and inspiration from ddvk/rmapi.