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create_text

Add new text elements to Figma designs by specifying content, position, font size, weight, and color through structured input via cursor AI integration.

Instructions

Create a new text element in Figma

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fontColorNoFont color in RGBA format
fontSizeNoFont size (default: 14)
fontWeightNoFont weight (e.g., 400 for Regular, 700 for Bold)
nameNoOptional name for the text node by default following text
parentIdNoOptional parent node ID to append the text to
textYesText content
xYesX position
yYesY position

Implementation Reference

  • Registration of the 'create_text' MCP tool using server.tool(), including schema and handler.
    server.tool(
      "create_text",
      "Create a new text element in Figma",
      {
        x: z.number().describe("X position"),
        y: z.number().describe("Y position"),
        text: z.string().describe("Text content"),
        fontSize: z.number().optional().describe("Font size (default: 14)"),
        fontWeight: z
          .number()
          .optional()
          .describe("Font weight (e.g., 400 for Regular, 700 for Bold)"),
        fontColor: z
          .object({
            r: z.number().min(0).max(1).describe("Red component (0-1)"),
            g: z.number().min(0).max(1).describe("Green component (0-1)"),
            b: z.number().min(0).max(1).describe("Blue component (0-1)"),
            a: z
              .number()
              .min(0)
              .max(1)
              .optional()
              .describe("Alpha component (0-1)"),
          })
          .optional()
          .describe("Font color in RGBA format"),
        name: z
          .string()
          .optional()
          .describe("Semantic layer name for the text node"),
        parentId: z
          .string()
          .optional()
          .describe("Optional parent node ID to append the text to"),
      },
      async ({ x, y, text, fontSize, fontWeight, fontColor, name, parentId }: any) => {
        try {
          const result = await sendCommandToFigma("create_text", {
            x,
            y,
            text,
            fontSize: fontSize || 14,
            fontWeight: fontWeight || 400,
            fontColor: fontColor || { r: 0, g: 0, b: 0, a: 1 },
            name: name || "Text",
            parentId,
          });
          const typedResult = result as { name: string; id: string };
          return {
            content: [
              {
                type: "text",
                text: `Created text "${typedResult.name}" with ID: ${typedResult.id}`,
              },
            ],
          };
        } catch (error) {
          return {
            content: [
              {
                type: "text",
                text: `Error creating text: ${error instanceof Error ? error.message : String(error)
                  }`,
              },
            ],
          };
        }
      }
    );
  • The handler function that executes the create_text tool logic by calling sendCommandToFigma('create_text') with provided parameters and handling the response.
    async ({ x, y, text, fontSize, fontWeight, fontColor, name, parentId }: any) => {
      try {
        const result = await sendCommandToFigma("create_text", {
          x,
          y,
          text,
          fontSize: fontSize || 14,
          fontWeight: fontWeight || 400,
          fontColor: fontColor || { r: 0, g: 0, b: 0, a: 1 },
          name: name || "Text",
          parentId,
        });
        const typedResult = result as { name: string; id: string };
        return {
          content: [
            {
              type: "text",
              text: `Created text "${typedResult.name}" with ID: ${typedResult.id}`,
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: `Error creating text: ${error instanceof Error ? error.message : String(error)
                }`,
            },
          ],
        };
      }
    }
  • Zod schema defining the input parameters for the create_text tool.
    {
      x: z.number().describe("X position"),
      y: z.number().describe("Y position"),
      text: z.string().describe("Text content"),
      fontSize: z.number().optional().describe("Font size (default: 14)"),
      fontWeight: z
        .number()
        .optional()
        .describe("Font weight (e.g., 400 for Regular, 700 for Bold)"),
      fontColor: z
        .object({
          r: z.number().min(0).max(1).describe("Red component (0-1)"),
          g: z.number().min(0).max(1).describe("Green component (0-1)"),
          b: z.number().min(0).max(1).describe("Blue component (0-1)"),
          a: z
            .number()
            .min(0)
            .max(1)
            .optional()
            .describe("Alpha component (0-1)"),
        })
        .optional()
        .describe("Font color in RGBA format"),
      name: z
        .string()
        .optional()
        .describe("Semantic layer name for the text node"),
      parentId: z
        .string()
        .optional()
        .describe("Optional parent node ID to append the text to"),
    },
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Create a new text element' implies a write/mutation operation, but the description doesn't mention permissions needed, whether this requires being in edit mode, what happens on failure, or any rate limits. For a mutation tool with zero annotation coverage, this is insufficient.

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?

The description is a single, efficient sentence that states the core purpose without any wasted words. It's appropriately sized and front-loaded with the essential information.

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

Completeness2/5

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

For a mutation tool with 8 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what happens after creation (e.g., returns a node ID), doesn't mention error conditions, and provides no context about the Figma environment needed for successful execution. The description should do more given the complexity.

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 description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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

Purpose4/5

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

The description clearly states the action ('Create') and resource ('new text element in Figma'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'set_text_content' or 'clone_node' that might also create or modify text elements, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'set_text_content' (which might update existing text) and 'clone_node' (which might duplicate text), there's no indication of when this specific creation tool is appropriate versus those other options.

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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