Skip to main content
Glama
index.ts5.79 kB
#!/usr/bin/env node /** * OpenAI MCP Server * * This is the main entry point for the OpenAI MCP server. It sets up the MCP server * with tools for interacting with OpenAI's APIs, particularly the DALL-E image generation API. * * The server can be run in two modes: * 1. Serve mode: Starts the MCP server to handle requests from MCP clients * 2. Install mode: Installs the MCP server configuration for Roo Code or Claude Desktop */ import { Server } from '@modelcontextprotocol/sdk/server/index.js'; import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js'; import { CallToolRequestSchema, ErrorCode, ListToolsRequestSchema, McpError, } from '@modelcontextprotocol/sdk/types.js'; import { Command } from 'commander'; import { generateImage, DalleRequest } from './dalle.js'; import { installMcpServer } from './install.js'; // Define the OpenAI API key environment variable const OPENAI_API_KEY = process.env.OPENAI_API_KEY; /** * Main MCP server class for OpenAI API integration */ class OpenAIMcpServer { private server: Server; constructor() { // Initialize the MCP server this.server = new Server( { name: 'openai-mcp', version: '1.1.0', }, { capabilities: { tools: {}, }, } ); // Set up request handlers this.setupToolHandlers(); // Set up error handling this.server.onerror = (error) => console.error('[MCP Error]', error); process.on('SIGINT', async () => { await this.server.close(); process.exit(0); }); } /** * Set up MCP tool handlers for OpenAI API integration */ private setupToolHandlers() { // List available tools this.server.setRequestHandler(ListToolsRequestSchema, async () => ({ tools: [ { name: 'generate_image', description: 'Generate an image using OpenAI\'s DALL-E API', inputSchema: { type: 'object', properties: { prompt: { type: 'string', description: 'Text description of the desired image', }, model: { type: 'string', description: 'DALL-E model to use (dall-e-2 or dall-e-3)', enum: ['dall-e-2', 'dall-e-3'], }, n: { type: 'number', description: 'Number of images to generate (1-10)', minimum: 1, maximum: 10, }, size: { type: 'string', description: 'Size of the generated image', enum: ['256x256', '512x512', '1024x1024', '1792x1024', '1024x1792'], }, quality: { type: 'string', description: 'Quality of the generated image', enum: ['standard', 'hd'], }, style: { type: 'string', description: 'Style of the generated image', enum: ['vivid', 'natural'], }, response_format: { type: 'string', description: 'Format of the response', enum: ['url', 'b64_json'], }, user: { type: 'string', description: 'A unique identifier for the end-user', }, }, required: ['prompt'], }, }, ], })); // Handle tool calls this.server.setRequestHandler(CallToolRequestSchema, async (request) => { if (request.params.name !== 'generate_image') { throw new McpError( ErrorCode.MethodNotFound, `Unknown tool: ${request.params.name}` ); } // Check if API key is provided if (!OPENAI_API_KEY) { throw new McpError( ErrorCode.InternalError, 'OPENAI_API_KEY environment variable is required' ); } try { // Generate the image using DALL-E API const response = await generateImage( OPENAI_API_KEY, request.params.arguments as DalleRequest ); // Format the response for MCP return { content: [ { type: 'text', text: JSON.stringify({ created: response.created, url: response.data[0].url, revised_prompt: response.data[0].revised_prompt, }, null, 2), }, ], }; } catch (error) { // Handle errors if (error instanceof Error) { return { content: [ { type: 'text', text: error.message, }, ], isError: true, }; } throw error; } }); } /** * Run the MCP server */ async run() { const transport = new StdioServerTransport(); await this.server.connect(transport); console.error('OpenAI MCP server running on stdio'); } } // Set up command-line interface const program = new Command(); program .name('openai-mcp') .description('MCP server for OpenAI API integration') .version('1.1.0'); // Serve command - starts the MCP server program .command('serve') .description('Start the MCP server') .action(() => { const server = new OpenAIMcpServer(); server.run().catch(console.error); }); // Install command - installs the MCP server configuration program .command('install') .description('Install the MCP server configuration for Roo Code or Claude Desktop') .action(() => { installMcpServer(); }); // Parse command-line arguments program.parse();

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jezweb/openai-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server