Skip to main content
Glama
praveensehgal

io.github.praveensehgal/remarkable

remarkable_image

Read-onlyIdempotent

Render a notebook or document page as a PNG or SVG image to view hand-drawn diagrams, sketches, or UI mockups from your reMarkable tablet.

Instructions

Get an image of a specific page from a reMarkable document. Renders a notebook or document page as an image (PNG or SVG). This is useful for:

  • Viewing hand-drawn diagrams, sketches, or UI mockups

  • Getting visual context that text extraction might miss

  • Implementing designs based on hand-drawn wireframes

  • SVG format for scalable vector graphics that can be edited

Response Formats

By default, images are returned as embedded resources (EmbeddedResource) which include the full image data inline:

  • PNG: Returned as BlobResourceContents with base64-encoded data

  • SVG: Returned as TextResourceContents with SVG markup

If your client doesn't support embedded resources in tool responses, set compatibility=True to receive a JSON response with just the resource URI. The client can then fetch the resource separately.

Optionally, enable include_ocr=True to extract text from the image using OCR. When REMARKABLE_OCR_BACKEND=sampling is set and the client supports sampling, the client's own LLM will be used for OCR (no API keys needed).

Note: This works best with notebooks and handwritten content. For PDFs/EPUBs, the annotations layer is rendered (not the underlying PDF content).

  • document: Document name or path (use remarkable_browse to find documents)

  • page: Page number (default: 1, 1-indexed)

  • background: Background color as hex code. Supports RGB (#RRGGBB) or RGBA (#RRGGBBAA). Default is "#FBFBFB" (reMarkable paper color), or set REMARKABLE_BACKGROUND_COLOR env var to override. Use "#00000000" for transparent.

  • output_format: Output format - "png" (default) or "svg" for vector graphics

  • compatibility: If True, return resource URI in JSON instead of embedded resource. Use this if your client doesn't support embedded resources in tool responses.

  • include_ocr: Enable OCR text extraction from the image (default: False). When REMARKABLE_OCR_BACKEND=sampling, uses the client's LLM via MCP sampling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentYes
pageNo
backgroundNo
output_formatNopng
compatibilityNo
include_ocrNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark it as read-only, idempotent. Description adds detail on response formats (embedded resource vs. compatibility JSON), OCR behavior, background color defaults, and PDF/EPUB annotation-only rendering. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with <usecase>, <instructions>, <parameters>, <examples>. Slightly verbose with multiple examples but still efficient. Front-loads key info.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, no output schema, and good annotations, description covers all user needs: resource fetching, OCR, background customization, and document finding via sibling tool. Complete for its complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has zero descriptions (0% coverage). Description fully explains all 6 parameters with defaults, format details, and env var option for background. Example usage reinforces parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it gets an image of a specific reMarkable page. Lists specific use cases (diagrams, sketches, wireframes) and contrasts with tools like remarkable_read for text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit context for use (hand-drawn content, visual context). Notes limitation for PDFs/EPUBs (only annotations rendered). Lacks explicit mention of alternatives like remarkable_read for text extraction, but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/praveensehgal/remarkable-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server