reMarkable MCP Server

io.github.wavyrai由 GitHub 帳號 wavyrai 發布v0.7.0更新於 Oct 27, 2026

Access your reMarkable tablet - read documents, browse files, extract text and OCR handwritten notes

概覽

AI 產生的概覽

透過 reMarkable 雲端 API 把 AI 助理接上 reMarkable 平板書庫,可瀏覽、閱讀、搜尋文件並對筆記做 OCR。

可以做什麼
  • 瀏覽資料夾、查看最近修改的文件
  • 讀取並擷取文件、PDF 與 EPUB 文字,支援頁碼範圍、分頁與依關鍵字跳頁
  • 跨多份文件搜尋內容,閱讀後自動建立全文索引
  • 將頁面渲染成 PNG 或 SVG 影像以提供視覺脈絡
  • 透過 MCP sampling 由用戶端模型對筆記做手寫 OCR
  • 重新命名、移動與新增資料夾(不會刪除內容),並把文件註冊為 MCP 資源
適用情境
適合筆記、研究資料或日誌存放在 reMarkable 平板,希望助理協助摘要、檢索,或把內容整理進 Obsidian 等寫作與知識管理工作流程的情境。
執行需求
以本機 Python 套件(uvx rm-mcp)透過 stdio 執行。需要 reMarkable Connect 訂閱,並透過 setup 或 register 指令取得 REMARKABLE_TOKEN。OCR 需要用戶端支援 sampling 能力。選用變數可限定根目錄、開啟唯讀模式,以及調整快取與輸出大小。
安裝前請注意
此權杖可存取你的 reMarkable 雲端書庫,請勿寫入共用設定。重新命名、移動與新增資料夾預設為開啟,若要唯讀請將 REMARKABLE_READ_ONLY 設為 1。啟用 OCR 時頁面影像會經 sampling 傳送給用戶端模型。文件文字會存入本機 SQLite 索引。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 reMarkable MCP Server,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

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
  • Organise your library — Rename, move, and create folders (nothing is ever deleted)
  • 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

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

One-command setup (recommended)

bash
uvx rm-mcp --setup

This opens your browser, prompts for the one-time code, and prints the ready-to-paste config for Claude Code and Claude Desktop.

Manual setup

1. Get a One-Time Code

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

2. Convert to Token
bash
uvx rm-mcp --register YOUR_CODE
3. Add to your MCP client

Claude Code:

bash
claude mcp add remarkable \  -e REMARKABLE_TOKEN='<paste token from step 2>' \  -e REMARKABLE_OCR_BACKEND=sampling \  -- uvx rm-mcp@latest

Claude Desktop — add to claude_desktop_config.json (use full path to uvx, e.g. from which uvx):

json
{  "mcpServers": {    "remarkable": {      "command": "/Users/YOU/.local/bin/uvx",      "args": ["rm-mcp@latest"],      "env": {        "REMARKABLE_TOKEN": "<paste token from step 2>"      }    }  }}


Tools

ToolDescription
remarkable_readRead and extract text from documents (with pagination and search)
remarkable_browseNavigate folders in your library
remarkable_searchSearch content across multiple documents
remarkable_recentGet recently modified documents
remarkable_statusCheck connection status
remarkable_imageGet 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

  • Multi-page read — Read all pages at once with pages="all", or a range like pages="1-3"
  • Grep auto-redirect — grep automatically finds and jumps to the matching page
  • Auto-redirect — Browsing a document path returns its content automatically
  • Auto-OCR — Notebooks with no typed text automatically enable OCR (opt out with auto_ocr=False)
  • Full-text search — Reading a document indexes it for fast future searches
  • Compact mode — Use compact_output=True to reduce token usage in responses
  • 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 documentremarkable_read("Meeting Notes")
# Read all pages at onceremarkable_read("Meeting Notes", pages="all")
# Read a range of pagesremarkable_read("Research Paper", pages="1-3")
# Search for keywords (auto-redirects to matching page)remarkable_read("Project Plan", grep="deadline")
# Enable OCR for handwritten notesremarkable_read("Journal", include_ocr=True)
# Browse your libraryremarkable_browse("/Work/Projects")
# Search across documentsremarkable_search("meeting", grep="action items")
# Get recent documents with previewsremarkable_recent(limit=5, include_preview=True)
# Get a page imageremarkable_image("UI Mockup", page=1)
# Get image with OCR text extractionremarkable_image("Handwritten Notes", include_ocr=True)

Resources

Documents are automatically registered as MCP resources:

URI SchemeDescription
remarkable:///{path}.txtExtracted text content
remarkableimg:///{path}.page-{N}.pngPNG image of page N (notebooks only)
remarkablesvg:///{path}.page-{N}.svgSVG 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

python
# OCR on a page imageremarkable_image("Handwritten Notes", include_ocr=True)
# OCR when reading a notebookremarkable_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.

All Environment Variables

VariableDefaultDescription
REMARKABLE_TOKEN(required)Auth token from uvx rm-mcp --setup
REMARKABLE_ROOT_PATH/Limit access to a specific folder
REMARKABLE_READ_ONLY(off)Set to 1 to disable renaming, moving and creating folders
REMARKABLE_OCR_BACKENDsamplingOCR backend (sampling)
REMARKABLE_BACKGROUND_COLOR#FBFBFBBackground color for rendered images (#RRGGBB or #RRGGBBAA)
REMARKABLE_CACHE_TTL60Collection cache TTL in seconds
REMARKABLE_COMPACT(off)Set to 1 or true to omit hints from responses globally
REMARKABLE_MAX_OUTPUT_CHARS50000Maximum characters in tool responses
REMARKABLE_PAGE_SIZE8000PDF/EPUB page size in characters
REMARKABLE_PARALLEL_WORKERS5Parallel workers for metadata fetching
REMARKABLE_INDEX_CONTENT1Set to 0 to disable background indexing of PDF/EPUB text
REMARKABLE_INDEX_PATH~/.cache/rm-mcp/index.dbSQLite full-text search index location
REMARKABLE_INDEX_REBUILD(off)Set to 1 to force index rebuild on startup

Most users only need REMARKABLE_TOKEN. The rest are for advanced tuning.


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

GuideDescription
Tools ReferenceDetailed tool documentation
Resources ReferenceMCP resources documentation
Capability NegotiationMCP protocol capabilities
DevelopmentContributing and development setup
Future PlansRoadmap and planned features

Development

bash
git clone https://github.com/wavyrai/rm-mcp.gitcd rm-mcpuv sync --all-extrasuv run pytest test_server.py -v

📖 Development Guide


License

MIT


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

來源:README.md,提交 8e0f74d

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.7.0最新Sep 16, 2026

評分

已滿足適用檢查項的 50%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通25 分

    請保持端點能夠回應 MCP 握手;SourceWeft 每 30 天探測一次。

  • 已宣告認證方式10 分

    請在註冊中心條目中宣告憑證請求標頭,或保持端點能夠回應探測,以便判定其認證方式。

  • 已列出工具15 分

    請讓伺服器在無憑證時回應 tools/list,或發布可在沙箱中無憑證啟動的軟體包。

  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分