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figma-console-mcp

by southleft

figma_capture_screenshot

Captures a Figma node's current runtime state as an AI-ready screenshot, enabling immediate validation of applied design changes.

Instructions

Capture a screenshot of a node using the plugin's exportAsync API. IMPORTANT: This tool captures the CURRENT state from the plugin runtime (not cloud state like REST API), making it reliable for validating changes immediately after making them. Use this instead of figma_get_component_image when you need to verify that changes were applied correctly. Defaults are AI-optimized: PNG at 1x with automatic downscaling so the longest side stays within the 1568px AI vision processing ceiling. PNG is the default because design tool content (flat colors, text, UI components) compresses significantly better as PNG. Use JPG for photographic or gradient-heavy content. Requires Desktop Bridge connection (Figma Desktop with plugin running).

Input Schema

NameRequiredDescriptionDefault
scaleNoScale factor (default: 1). The plugin automatically caps the effective scale so the exported image does not exceed 1568px on its longest side (the AI vision processing ceiling).
formatNoImage format (default: PNG). Use JPG for photographic or gradient-heavy content.PNG
nodeIdNoID of the node to capture (e.g., '1:234'). If not provided, captures the current page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.46.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description does substantial work: it discloses that captures reflect current plugin-runtime state rather than cloud state, that downscaling is automatically applied to stay under the AI vision ceiling, and that a Desktop Bridge connection is required. It stops short of describing the return payload 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.

Conciseness4/5

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

The description is front-loaded with the core action and the important runtime-state caveat. Some sentences, such as the PNG compression rationale and JPG guidance, overlap with schema documentation or could be trimmed, but the overall structure is clear.

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?

For a three-parameter screenshot tool with no annotations and no output schema, it covers the key context: plugin-runtime state, connection prerequisites, default export behavior, and an alternative tool. Return format and error behavior are not described, which keeps it from being fully complete.

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?

Schema coverage is 100%, so all three parameters, their defaults, and the format enum are already documented in the schema. The description reinforces the AI-optimized defaults and format-choice rationale, but it largely repeats schema content rather than adding new 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?

The description states a specific verb and resource: capture a screenshot of a node using the plugin's exportAsync API. It also distinguishes plugin-runtime capture from cloud-state alternatives and explicitly contrasts itself with figma_get_component_image, making the tool's purpose easy to identify.

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

Usage Guidelines5/5

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

It gives explicit usage guidance: use this tool to validate changes immediately after making them, and use it instead of figma_get_component_image when verifying applied changes. It also explains the current-plugin-runtime context and when to choose JPG over PNG.

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

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