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paragdesai1

Cursor Talk to Figma MCP

by paragdesai1

get_selection

Retrieve details about currently selected elements in Figma designs to enable programmatic reading and modification through Cursor AI integration.

Instructions

Get information about the current selection in Figma

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Registers the MCP tool 'get_selection'. The handler is a thin proxy that calls sendCommandToFigma("get_selection") via WebSocket to the Figma plugin and returns the result as text content.
    server.tool(
      "get_selection",
      "Get information about the current selection in Figma",
      {},
      async () => {
        try {
          const result = await sendCommandToFigma("get_selection");
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify(result)
              }
            ]
          };
        } catch (error) {
          return {
            content: [
              {
                type: "text",
                text: `Error getting selection: ${error instanceof Error ? error.message : String(error)
                  }`,
              },
            ],
          };
        }
      }
    );
  • Core handler implementation in Figma plugin. Returns the count of selected nodes and array of basic info objects (id, name, type, visible) from figma.currentPage.selection.
    async function getSelection() {
      return {
        selectionCount: figma.currentPage.selection.length,
        selection: figma.currentPage.selection.map((node) => ({
          id: node.id,
          name: node.name,
          type: node.type,
          visible: node.visible,
        })),
      };
    }
  • Dispatch in handleCommand switch statement that routes 'get_selection' commands to the getSelection() handler.
    case "get_selection":
      return await getSelection();
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get information', implying a read-only operation, but doesn't clarify aspects like whether it requires specific permissions, what format the information is returned in, or if there are any rate limits. This leaves significant gaps in understanding the tool's behavior.

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, clear sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded with the core action and resource, making it efficient and easy to parse for an AI agent.

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

Completeness3/5

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

Given the tool has 0 parameters, no output schema, and no annotations, the description is minimally adequate by stating what it does. However, it lacks details on return values, error conditions, or behavioral nuances, which could be important for a tool interacting with a design environment like Figma. It meets the basic requirement but leaves room for improvement in completeness.

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?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, as there are none to explain. It appropriately focuses on the tool's purpose without redundant information, earning a baseline score for parameter-less tools.

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 verb 'Get' and the resource 'information about the current selection in Figma', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_node_info' or 'get_nodes_info', which might retrieve similar information but for different scopes or inputs.

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, such as 'get_node_info' or 'get_nodes_info', which could be used for similar purposes but with different parameters. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.

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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