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Letz AI MCP

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by Letz-AI
tools.ts7.44 kB
import axios from "axios"; import { convertImageUrlToBase64 } from "./utils/convertImageToBase64.js"; import { Server } from "@modelcontextprotocol/sdk/server/index.js"; import { CallToolRequestSchema, ListToolsRequestSchema, } from "@modelcontextprotocol/sdk/types.js"; import open from "open"; import { createImageTool, modes } from "./tools/createImage.js"; import { upscaleImageTool } from "./tools/upscaleImage.js"; export const setTools = (server: Server) => { server.setRequestHandler(ListToolsRequestSchema, async () => { return { tools: [createImageTool, upscaleImageTool], }; }); server.setRequestHandler( CallToolRequestSchema, async (request, connection) => { if (request.params.name === "letzai_create_image") { try { let { prompt, width, height, quality, creativity, hasWatermark, systemVersion, mode, } = request.params.arguments as any; mode = !mode || !mode.includes(mode || "") ? "turbo" : mode; width = parseInt(width) || 1600; height = parseInt(height) || 1600; quality = parseInt(quality) || 2; creativity = parseInt(creativity) || 2; systemVersion = parseInt(systemVersion) || 3; hasWatermark = typeof hasWatermark === "boolean" ? hasWatermark : false; // Step 1: Create the image request const responseCreate = await axios.post( "https://api.letz.ai/images", { prompt, width, height, quality, creativity, hasWatermark, systemVersion, mode, }, { headers: { Authorization: `Bearer ${process.env.LETZAI_API_KEY}`, }, } ); let imageFinished = false; let imageVersions: { original: string; "96x96": string; "240x240": string; "640x640": string; "1920x1920": string; } | null = null; let imageId = responseCreate.data.id; // Step 2: Poll for image creation status while (!imageFinished) { await new Promise((resolve) => setTimeout(resolve, 5000)); // Wait before checking again const responseImage = await axios.get( `https://api.letz.ai/images/${imageId}`, { headers: { Authorization: `Bearer ${process.env.LETZAI_API_KEY}`, }, } ); if (responseImage.data.progress < 100) { // Send a progress notification (through stdout for Stdio transport) console.log( JSON.stringify({ jsonrpc: "2.0", method: "progress_update", params: { message: `Image is still being processed. Progress: ${responseImage.data.progress}%`, }, }) ); } else { imageFinished = true; imageVersions = responseImage.data.imageVersions; } } // Convert the image to Base64 after processing is complete /* const imageBase64 = convertImageUrlToBase64( imageVersions?.["640x640"] as string ); */ // Open the image in browser open(imageVersions?.original as string); // Return the response to the client return { content: [ { type: "text", text: `Image generated successfully!\nThe image has been opened in your default browser.\n\n Image URL: ${imageVersions?.original}\n\nYou can also click the URL above to view the image again.`, }, ], }; } catch (err: any) { return { content: [ { type: "text", text: `Error happened: ${err.toString()}`, }, ], }; } } else if (request.params.name === "letzai_upscale_image") { try { let { imageId, imageUrl, strength } = request.params.arguments as any; strength = parseInt(strength) || 1; let body = {}; if (imageId) { body = { imageId, strength, }; } else if (imageUrl) { body = { imageUrl, strength, }; } else { throw new Error("Provide image ID or Image URL"); } // Step 1: Create the image request const responseCreate = await axios.post( "https://api.letz.ai/upscale", body, { headers: { Authorization: `Bearer ${process.env.LETZAI_API_KEY}`, }, } ); let imageFinished = false; let imageVersions: { original: string; "96x96": string; "240x240": string; "640x640": string; "1920x1920": string; } | null = null; let upscaleId = responseCreate.data.id; // Step 2: Poll for image creation status while (!imageFinished) { await new Promise((resolve) => setTimeout(resolve, 5000)); // Wait before checking again const responseImage = await axios.get( `https://api.letz.ai/upscale/${upscaleId}`, { headers: { Authorization: `Bearer ${process.env.LETZAI_API_KEY}`, }, } ); if (responseImage.data.status != "ready") { // Send a progress notification (through stdout for Stdio transport) console.log( JSON.stringify({ jsonrpc: "2.0", method: "progress_update", params: { message: `Image is still being processed. Progress: ${responseImage.data.progress}%`, }, }) ); } else { imageFinished = true; imageVersions = responseImage.data.imageVersions; } } // Convert the image to Base64 after processing is complete /* const imageBase64 = convertImageUrlToBase64( imageVersions?.["640x640"] as string ); */ // Open the image in browser open(imageVersions?.original as string); // Return the response to the client return { content: [ { type: "text", text: `Image upscaled successfully!\nThe image has been opened in your default browser.\n\n Image URL: ${imageVersions?.original}\n\nYou can also click the URL above to view the image again.`, }, ], }; } catch (err: any) { return { content: [ { type: "text", text: `Error happened: ${err.toString()}`, }, ], }; } } throw new Error("Tool not found"); } ); };

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