MCP server for accessing reMarkable tablet data
Project description
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.
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
}
],
"servers": {
"remarkable": {
"command": "uvx",
"args": ["rm-mcp"],
"env": {
"REMARKABLE_TOKEN": "${input:remarkable-token}"
}
}
}
}
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.
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)
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
OCR for Handwriting
rm-mcp uses sampling OCR — your MCP client's AI model extracts text from handwritten notes. No additional API keys or services needed.
How It Works
When you use include_ocr=True, rm-mcp sends page images to your client's LLM (Claude, GPT-4, etc.) via MCP sampling. The model reads the handwriting and returns the text.
Usage
# OCR on a page image
remarkable_image("Handwritten Notes", include_ocr=True)
# OCR when reading a notebook
remarkable_read("Journal", include_ocr=True)
Requirements
- Your MCP client must support the sampling capability (VS Code + Copilot, Claude Desktop, etc.)
REMARKABLE_OCR_BACKEND=sampling(this is the default)
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"
}
}
}
}
With this configuration:
remarkable_browse("/")shows contents of/Workremarkable_browse("/Projects")shows/Work/Projects- Documents outside
/Workare 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.,#FFFFFFfor white)#RRGGBBAA— RGBA hex (e.g.,#00000000for transparent)
Default is #FBFBFB (reMarkable paper color). This affects both the remarkable_image tool and image resources.
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.
Documentation
| Guide | Description |
|---|---|
| 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 |
Development
git clone https://github.com/wavyrai/rm-mcp.git
cd rm-mcp
uv sync --all-extras
uv run pytest test_server.py -v
License
MIT
Built with rmscene, PyMuPDF, and inspiration from ddvk/rmapi.
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