Metadata-Version: 2.4
Name: rm-mcp
Version: 0.3.1
Summary: MCP server for accessing reMarkable tablet data
Author: Thijs Verreck
License: MIT
License-File: LICENSE
Keywords: mcp,notes,remarkable,tablet
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.10
Requires-Dist: beautifulsoup4>=4.12.0
Requires-Dist: cairosvg>=2.8.2
Requires-Dist: ebooklib>=0.18
Requires-Dist: mcp>=1.0.0
Requires-Dist: pillow>=10.0.0
Requires-Dist: pymupdf>=1.24.0
Requires-Dist: requests>=2.28.0
Requires-Dist: rmc>=0.3.0
Requires-Dist: rmscene>=0.6.0
Provides-Extra: dev
Requires-Dist: black>=23.0.0; extra == 'dev'
Requires-Dist: pytest-asyncio>=1.0.0; extra == 'dev'
Requires-Dist: pytest>=7.0.0; extra == 'dev'
Requires-Dist: ruff>=0.1.0; extra == 'dev'
Description-Content-Type: text/markdown

# 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.

<!-- mcp-name: io.github.wavyrai/rm-mcp -->

## 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](https://my.remarkable.com/device/browser/connect) and generate a code.

#### 2. Convert to Token

```bash
uvx rm-mcp --register YOUR_CODE
```

#### 3. Install

[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=for-the-badge&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=remarkable&inputs=%5B%7B%22type%22%3A%22promptString%22%2C%22id%22%3A%22token%22%2C%22description%22%3A%22reMarkable%20API%20token%22%2C%22password%22%3Atrue%7D%5D&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22rm-mcp%22%5D%2C%22env%22%3A%7B%22REMARKABLE_TOKEN%22%3A%22%24%7Binput%3Atoken%7D%22%7D%7D)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=for-the-badge&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=remarkable&inputs=%5B%7B%22type%22%3A%22promptString%22%2C%22id%22%3A%22token%22%2C%22description%22%3A%22reMarkable%20API%20token%22%2C%22password%22%3Atrue%7D%5D&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22rm-mcp%22%5D%2C%22env%22%3A%7B%22REMARKABLE_TOKEN%22%3A%22%24%7Binput%3Atoken%7D%22%7D%7D&quality=insiders)

Or configure manually in `.vscode/mcp.json`:

```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}"
      }
    }
  }
}
```

---

<!-- Screenshots section - uncomment when screenshots are added
## Screenshots

### MCP Resources

Documents appear as resources that AI assistants can access directly:

![Resources in VS Code](docs/assets/resources-screenshot.png)

### Tool Calls in Action

AI assistants use the tools to read documents, search content, and more:

![Tool calls in VS Code](docs/assets/tool-calls-screenshot.png)
-->

---

## 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](docs/tools.md)**

### 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

```python
# 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](docs/resources.md)**

---

## 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

```python
# 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:

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

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:

```json
{
  "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.

---

## 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](docs/tools.md) | Detailed tool documentation |
| [Resources Reference](docs/resources.md) | MCP resources documentation |
| [Capability Negotiation](docs/capabilities.md) | MCP protocol capabilities |
| [Development](docs/development.md) | Contributing and development setup |
| [Future Plans](docs/future-plans.md) | Roadmap and planned features |

---

## Development

```bash
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](docs/development.md)**

---

## License

MIT

---

Built with [rmscene](https://github.com/ricklupton/rmscene), [PyMuPDF](https://pymupdf.readthedocs.io/), and inspiration from [ddvk/rmapi](https://github.com/ddvk/rmapi).
