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figma-reader-mcp

by LeoGCode

figma_screenshot

Render a Figma node as a PNG image from the live browser file, returning it downscaled to a specified size. Use this to capture design elements without touching the system clipboard.

Instructions

Render a node to PNG using Figma's own 'Copy as PNG' in the browser (the system clipboard is not touched). Uses the live file, not the snapshot. Returns the image, downscaled to max_dimension.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesA Figma file key or figma.com/design/... URL (a node-id in the URL is used when node_id is omitted). The image always comes from the live file in the browser, so a local .fig path works only if its name carries the key ('<name> [<key>].fig'), and is read only to tell whether node_id is a page.
node_idNo
save_pathNoAlso save the PNG (at returned size) to this path
max_dimensionNoLongest side in px of the returned image (default 1568)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Beyond the annotations, the description adds valuable behavioral detail: the system clipboard is not touched, the live file is used instead of a snapshot, and the returned image is downscaled to max_dimension. This provides meaningful transparency about side effects and data source, though it doesn't cover auth or failure modes.

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?

Three short sentences, each carrying distinct information: rendering method, side-effect negation, source, and output scaling. There is no filler, repetition, or unnecessary detail.

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 the absence of an output schema, the description conveys the core behavior—returns an image, downscaled, from the live file—and the key side-effect it avoids. It is slightly thin on edge cases like omitted node_id or error behavior, but the schema covers file format details, so an agent has enough to call it correctly.

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

Parameters3/5

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

The input schema already provides descriptions for 75% of parameters, and the tool description mostly restates or reinforces that information, such as downscaling to max_dimension and using the live file. It adds little meaning beyond the schema, and node_id remains only indirectly described.

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 states a specific verb ('Render'), a resource ('a node'), and an output format ('PNG'), making the tool's purpose immediately clear. It also distinguishes itself from snapshot-based or export-related siblings by noting it uses Figma's own 'Copy as PNG' with the live file, not the snapshot.

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 gives useful context, such as 'Uses the live file, not the snapshot,' which implies when this tool is appropriate, but it does not explicitly state when to use it versus alternatives or name exclusions. An agent must infer usage rather than receiving direct guidance.

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