Figma MCP — Trigger Specific Tools

The Figma MCP exposes multiple tools, each providing a different kind of structured context. As the tool count grows, AI assistants don't always pick the right one automatically — explicit prompt nudges fix this.

Key Tools

Tool	What it returns	When to trigger it
`get_design_context`	React + Tailwind structured representation of the selection	Starting point for code generation; translate to any framework after
`get_variable_defs`	Variables and styles (color, spacing, typography tokens)	When you need token names/values in generated code

The Problem

AI assistants often default to get_design_context even when you need variables. Users reported requesting variable values but getting raw code instead.

The Fix — Explicit Prompt

Instead of:

"Generate code for this frame"

Say:

"Get the variable names and values used in this frame"

Being explicit about what you want is enough to steer the model toward the correct tool.

Key Takeaways

AI tool selection is not deterministic — add intent to your prompts when output feels wrong or incomplete.
get_design_context = structure/layout → code generation starting point.
get_variable_defs = design tokens → use when you need exact color/spacing/type values in generated code.
Prompt pattern: name the artifact you want ("variable names and values", "design context", "screenshot") not just the end goal ("generate code").
If output is still off after nudging, check wiki/claude-code/figma-mcp-avoid-large-frames — large selections degrade tool output quality.

wiki/claude-code/figma-mcp-tools-reference — full reference for all 18 Figma MCP tools
wiki/claude-code/figma-mcp-avoid-large-frames — selection size affects output quality
wiki/claude-code/figma-mcp-custom-rules — lock in the right tool flow via CLAUDE.md rules
wiki/claude-code/figma-mcp-guide — Figma MCP overview and capabilities

Sources

raw/Trigger specific tools when needed.md (source: developers.figma.com/docs/figma-mcp-server/trigger-specific-tools/)

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