Skip to main content
Glama
wenym8

figmingo-mcp

by wenym8

get_screenshot

Renders a Figma node to an image (PNG, JPG, SVG, or PDF) with scale from 0.01 to 4. Returns base64 inline or saves to disk.

Instructions

Render a Figma node to an image via GET /v1/images/:fileKey (scale 0.01–4, png|jpg|svg|pdf). Returns the image inline (base64) and/or saves it to disk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoFull figma.com URL (design/file/proto). node-id query param is honored.
scaleNo
formatNopng
inlineNoReturn the image inline as base64 (default true).
nodeIdYesNode id to render, "1:2" or "1-2" form (or via url node-id).
fileKeyNoFigma file key (from the file URL). Provide either fileKey or url.
savePathNoOptional file path to save the render to.
Behavior4/5

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

With no annotations, the description carries full burden. It discloses that the tool returns base64 inline and/or saves to disk, and specifies valid inputs (scale range, formats). It does not mention authentication, error states, or read-only nature, but covers core behavioral aspects adequately.

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

Conciseness5/5

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

Two sentences with no wasted words. The first sentence immediately states the core purpose, and the second adds key options. It is front-loaded and efficient.

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

Completeness4/5

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

Given 7 parameters and no output schema or annotations, the description covers essential input choices and output behavior. It lacks detail on response format beyond 'base64' and error handling, but it is sufficiently complete for typical usage.

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

Parameters4/5

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

Schema coverage is 71%, and the description adds context beyond schema: it clarifies scale range, formats, and the choice between url/fileKey. It explains the output modes (inline base64, savePath) and that node-id can come from url. This helps an agent determine parameter values.

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?

The description clearly states the tool renders a Figma node to an image using the specified endpoint, and lists supported formats and output options. It distinguishes the tool from siblings (e.g., render_html_screenshot) by the resources and endpoint used.

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

Usage Guidelines3/5

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

The description provides technical details (scale, format, output modes) but does not explicitly state when to use this tool versus siblings like get_design_context or render_html_screenshot. No exclusion criteria or alternative suggestions are given.

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/wenym8/figmingo-mcp'

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