InputMCP

Instructions

Implementation Reference

• src/server.ts:30-75 (handler)

  The handler function for the 'collect_input' tool. Normalizes input parameters, launches the input prompt UI, processes the result (caching images), and returns MCP-formatted content or throws errors appropriately.
  }, async ({ kind, initialImage, gridWidth, gridHeight, width, height, message }) => { const baseSpec = normalizeSpec(kind); // Apply custom parameters const spec = { ...baseSpec, ...(initialImage && { initialImage }), ...(message && { message }), ...(baseSpec.kind === 'pixelart' && gridWidth && { gridWidth }), ...(baseSpec.kind === 'pixelart' && gridHeight && { gridHeight }), ...(baseSpec.kind === 'image' && width && { width }), ...(baseSpec.kind === 'image' && height && { height }) }; try { const result = await launchInputPrompt({ spec }); if (result.kind === "text") { return { content: [{ type: "text", text: result.value }] }; } if (result.kind === "image" || result.kind === "pixelart") { // Save image to cache const cachedPath = await saveImageToCache(result.dataUrl); // Return the file path as text instead of base64 image data return { content: [{ type: "text", text: cachedPath }], isError: false }; } throw new Error(`Unsupported input result kind: ${(result as { kind?: string } | undefined)?.kind ?? "unknown"}`); } catch (error) { if (error instanceof InputCancelledError) { throw new Error("User cancelled the input"); } if (error instanceof InputFailedError) { throw error; // Re-throw with original message } throw error; // Re-throw any other errors } });
• src/server.ts:19-29 (schema)

  Tool metadata including title, description, and inputSchema definition using Zod for validation of parameters like kind, dimensions, and message.
  title: "Collect Input", description: "get image, text, or pixel art input from user. This is used to get contextual input from the user of different kinds. ", inputSchema: { kind: z.enum(["text", "image", "pixelart"]).optional(), initialImage: z.string().optional().describe("Initial image to load for editing (file path)"), gridWidth: z.number().int().min(4).max(128).optional().describe("Grid width for pixel art (default: 16)"), gridHeight: z.number().int().min(4).max(128).optional().describe("Grid height for pixel art (default: 16)"), width: z.number().int().min(32).max(4096).optional().describe("Canvas width for image mode (default: 512)"), height: z.number().int().min(32).max(4096).optional().describe("Canvas height for image mode (default: 512)"), message: z.string().optional().describe("Custom message to show to the user") },
• src/server.ts:18-18 (registration)

  Registration of the 'collect_input' tool with the MCP server.
  server.registerTool("collect_input", {
• src/create.ts:108-181 (helper)

  Primary helper function that launches an Electron window with the UI for collecting input (text, image, or pixelart) based on the spec, captures the result via stdout, and resolves with SubmissionResult or rejects with errors.
  export async function launchInputPrompt({ spec }: { spec: InputSpec; }): Promise<SubmissionResult> { await ensureUiBuilt(); // Process initialImage if present let processedSpec = spec; if ((spec.kind === 'image' || spec.kind === 'pixelart') && spec.initialImage) { const dataURL = await loadImageAsDataURL(spec.initialImage); processedSpec = { ...spec, initialImage: dataURL }; } const electronModule: any = await import("electron"); const electronBinary = typeof electronModule === "string" ? electronModule : typeof electronModule.default === "string" ? electronModule.default : electronModule.path; if (!electronBinary) { throw new Error("Electron binary not found, make sure electron is installed"); } return new Promise<SubmissionResult>((resolvePromise, rejectPromise) => { const child = spawn(electronBinary, [electronEntrypoint], { stdio: ["ignore", "pipe", "inherit"], env: { ...process.env, MCP_INPUT_SPEC: JSON.stringify(processedSpec) } }); let stdout = ""; child.stdout.on("data", (chunk: Buffer) => { stdout += chunk.toString(); }); child.once("error", (error) => { rejectPromise(error); }); child.once("exit", (code) => { if (code !== 0) { rejectPromise(new InputFailedError(`Electron process exited with code ${code}`)); return; } if (!stdout.trim()) { rejectPromise(new InputFailedError("No response from Electron process")); return; } try { const parsed = JSON.parse(stdout); // Handle the different action types if (parsed.action === "submit") { resolvePromise(parsed.result); } else if (parsed.action === "cancel") { rejectPromise(new InputCancelledError()); } else if (parsed.action === "error") { rejectPromise(new InputFailedError(parsed.message)); } else { rejectPromise(new InputFailedError(`Unknown action: ${parsed.action}`)); } } catch (error) { rejectPromise(new InputFailedError(`Invalid JSON response: ${stdout}`)); } }); }); }
• src/create.ts:58-70 (helper)

  Helper function to normalize the input kind into a full InputSpec using Zod schemas with defaults.
  export function normalizeSpec(kind: InputKind | undefined): InputSpec { const resolved = kind ?? "text"; if (resolved === "image") { return ImageInputSpecSchema.parse({ kind: "image" }); } if (resolved === "pixelart") { return PixelArtInputSpecSchema.parse({ kind: "pixelart" }); } return TextInputSpecSchema.parse({ kind: "text" }); }