663 lines
26 KiB
JavaScript
663 lines
26 KiB
JavaScript
#!/usr/bin/env node
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/**
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* MCP image-gen server (thin custom wrapper around OpenRouter).
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*
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* Tools:
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* - generate_image(prompt, model, aspect) -> opaque PNG
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* - generate_image_transparent(prompt, model, aspect) -> PNG with alpha channel
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* - list_image_models() -> 35 image-capable models (1h cache)
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*
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* Auth: Bearer token in Authorization header (token from env MCP_TOKEN).
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*
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* Routing:
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* - sourceful/riverflow-* -> /api/v1/images (provider requires it)
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* - recraft/recraft-v* -> /api/v1/images (transparent_background flag)
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* - openai/gpt-image-* -> /chat/completions + image_config (background=transparent)
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* - everything else -> /chat/completions + modalities:[image,text]
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*
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* Design notes (from mcp-image-generation skill, validated 2026-07):
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* - Stateful StreamableHTTPServerTransport (sessionIdGenerator: crypto.randomUUID)
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* - try/catch around fetch AND transport.handleRequest
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* - AbortSignal.timeout(120_000) on upstream
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* - process.stderr.write on every request/response (SDK swallows errors)
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* - MODEL_CACHE 1h TTL
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*/
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import { Server } from '@modelcontextprotocol/sdk/server/index.js';
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import { StreamableHTTPServerTransport } from '@modelcontextprotocol/sdk/server/streamableHttp.js';
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import {
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ListToolsRequestSchema,
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CallToolRequestSchema,
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} from '@modelcontextprotocol/sdk/types.js';
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import { SSEServerTransport } from '@modelcontextprotocol/sdk/server/sse.js';
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import http from 'node:http';
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import crypto from 'node:crypto';
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import fs from 'node:fs/promises';
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import path from 'node:path';
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const API_KEY = process.env.OPENROUTER_API_KEY;
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const MCP_TOKEN = process.env.MCP_TOKEN;
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if (!API_KEY) {
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console.error('FATAL: OPENROUTER_API_KEY env not set');
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process.exit(1);
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}
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if (!MCP_TOKEN) {
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console.error('FATAL: MCP_TOKEN env not set (required to protect the endpoint)');
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process.exit(1);
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}
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const PORT = Number(process.env.PORT || 8935);
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const OUTPUT_DIR = process.env.IMAGE_MCP_OUTPUT_DIR || '/app/generated-images';
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// ---------- Models that support transparent background ----------
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// Recraft (v3 confirmed via OpenRouter /api/v1/images endpoint, accepts background param)
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// GPT-Image (1/2/5-image) via /chat/completions with image_config.background=transparent
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//
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// Order matters: riverflow check first because regex is more specific.
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const TRANSPARENT_MODELS = [
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'recraft/recraft-v3',
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'openai/gpt-image-1',
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'openai/gpt-image-1-mini',
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'openai/gpt-image-2',
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'openai/gpt-5-image',
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'openai/gpt-5-image-mini',
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];
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// ---------- Models known to accept image references (image-to-image / style refs) ----------
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// Order matters: more specific first.
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const IMAGE_REF_MODELS = new Set([
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// OpenAI
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'openai/gpt-image-1',
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'openai/gpt-image-1-mini',
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'openai/gpt-image-2',
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'openai/gpt-5-image',
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'openai/gpt-5-image-mini',
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'openai/gpt-5.4-image-2',
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// Google Gemini
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'google/gemini-2.5-flash-image',
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'google/gemini-3-pro-image',
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'google/gemini-3.1-flash-image',
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'google/gemini-3.1-flash-lite-image',
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'google/gemini-3.1-flash-image-preview',
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'google/gemini-3-pro-image-preview',
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// ByteDance Seedream (style ref supported via seed image)
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'bytedance-seed/seedream-4.5',
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// FLUX 2 (in editing variants)
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'black-forest-labs/flux.2-flex',
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'black-forest-labs/flux.2-pro',
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'black-forest-labs/flux.2-max',
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]);
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function isRiverflow(modelId) {
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return /^sourceful\/riverflow/i.test(modelId);
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}
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function isRecraft(modelId) {
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return /^recraft\//i.test(modelId);
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}
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function isGptImage(modelId) {
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return /^openai\/gpt-image-/i.test(modelId) || /^openai\/gpt-5-image/i.test(modelId);
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}
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function isTransparentCapable(modelId) {
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return TRANSPARENT_MODELS.includes(modelId);
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}
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// ---------- OpenRouter model catalog (cached 1h) ----------
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let MODEL_CACHE = null;
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let MODEL_CACHE_TIME = 0;
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const MODEL_TTL_MS = 3600_000;
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async function getImageModels() {
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if (MODEL_CACHE && Date.now() - MODEL_CACHE_TIME < MODEL_TTL_MS) {
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return MODEL_CACHE;
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}
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const r = await fetch(
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'https://openrouter.ai/api/v1/models?output_modalities=image',
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{ headers: { Authorization: `Bearer ${API_KEY}` } },
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);
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if (!r.ok) throw new Error(`OpenRouter /models ${r.status}`);
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const data = await r.json();
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MODEL_CACHE = data.data.map((m) => m.id);
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MODEL_CACHE_TIME = Date.now();
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process.stderr.write(`[cache] refreshed: ${MODEL_CACHE.length} image models\n`);
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return MODEL_CACHE;
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}
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function aspectToOpenRouter(ar) {
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if (ar === 'square') return '1:1';
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if (ar === 'landscape') return '16:9';
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if (ar === 'portrait') return '9:16';
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return ar;
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}
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// ---------- API call router ----------
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async function callOpenRouter({ prompt, model, aspect, transparent = false, imageUrls = [] }) {
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if (isRiverflow(model)) return await callRiverflowImages({ prompt, model, aspect, imageUrls });
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if (isRecraft(model)) return await callImagesEndpoint({ prompt, model, aspect, transparent, kind: 'recraft', imageUrls });
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if (isGptImage(model)) return await callImagesEndpoint({ prompt, model, aspect, transparent, kind: 'gpt-image', imageUrls });
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return await callChatCompletions({ prompt, model, aspect, imageUrls });
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}
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// Helper: validate that an image reference is acceptable.
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// Accepts http(s) URLs and data:image/... URLs. Anything else -> warn and drop.
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function normalizeImageUrls(rawUrls) {
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if (!Array.isArray(rawUrls)) return [];
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const out = [];
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for (const u of rawUrls) {
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if (typeof u !== 'string' || !u) continue;
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if (/^https?:\/\//i.test(u)) { out.push(u); continue; }
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if (/^data:image\//i.test(u)) { out.push(u); continue; }
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process.stderr.write(`[ref] skipping unsupported ref URL: ${u.slice(0, 80)}\n`);
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}
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return out;
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}
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// Build a multimodal user message for chat completions:
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// { role: 'user', content: [
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// { type: 'text', text: <prompt + aspect suffix> },
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// { type: 'image_url', image_url: { url: <ref> } }, ...
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// ] }
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function buildChatMessages({ prompt, aspect, imageUrls }) {
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const ar = aspectToOpenRouter(aspect);
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const text = ar ? `${prompt} (aspect ratio ${ar})` : prompt;
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const content = [{ type: 'text', text }];
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for (const url of imageUrls) {
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content.push({ type: 'image_url', image_url: { url } });
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}
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return [{ role: 'user', content }];
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}
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async function callChatCompletions({ prompt, model, aspect, imageUrls = [] }) {
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const resp = await fetch('https://openrouter.ai/api/v1/chat/completions', {
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method: 'POST',
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headers: {
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Authorization: `Bearer ${API_KEY}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model,
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messages: buildChatMessages({ prompt, aspect, imageUrls }),
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modalities: ['image', 'text'],
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}),
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signal: AbortSignal.timeout(120_000),
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});
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if (!resp.ok) {
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const body = await resp.text();
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throw new Error(`OpenRouter chat ${resp.status}: ${body.slice(0, 600)}`);
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}
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const data = await resp.json();
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const images = data.choices?.[0]?.message?.images;
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if (!images?.length) {
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const text = data.choices?.[0]?.message?.content;
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throw new Error(`No images returned. Text content: ${JSON.stringify(text).slice(0, 300)}`);
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}
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const imgEntry = images.find((e) => e?.image_url?.url?.startsWith('data:image/'));
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if (!imgEntry) throw new Error('images[] has no data: URLs (unsupported shape)');
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return {
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dataUrl: imgEntry.image_url.url,
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provider: 'chat_completions',
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mime: 'image/png',
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};
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}
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async function callImagesEndpoint({ prompt, model, aspect, transparent, kind, imageUrls = [] }) {
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// Same endpoint shape for Recraft and GPT-Image inside OpenRouter:
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// POST /api/v1/images
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// body: { model, prompt, size, n, background?, image? }
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//
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// image (single) / image[] (multiple refs) are routed by OpenRouter to models
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// that accept them. Recraft v3 supports 1 image ref. GPT-Image (chat completions
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// path) prefers the messages[] multimodal format — but OpenRouter also routes
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// a single `image` field for some providers. We pass the image_urls through
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// in BOTH places when supported to maximize compatibility — providers that
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// ignore the unused field will still receive the prompt.
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const sizeMap = {
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square: '1024x1024',
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landscape: '1536x1024',
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portrait: '1024x1536',
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};
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const body = {
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model,
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prompt,
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size: sizeMap[aspect] || '1024x1024',
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n: 1,
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};
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if (transparent) {
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// OpenAI Images API standard: "background": "transparent" (also accepts "opaque")
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body.background = 'transparent';
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}
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if (imageUrls.length > 0) {
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// OpenRouter accepts an array of reference image URLs via this top-level key.
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// Each provider may map it to its native convention (seed image, style ref, etc).
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body.image = imageUrls.length === 1 ? imageUrls[0] : imageUrls;
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}
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const resp = await fetch('https://openrouter.ai/api/v1/images', {
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method: 'POST',
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headers: {
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Authorization: `Bearer ${API_KEY}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify(body),
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signal: AbortSignal.timeout(120_000),
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});
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if (!resp.ok) {
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const errBody = await resp.text();
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throw new Error(
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`OpenRouter /api/v1/images (${kind}) ${resp.status}: ${errBody.slice(0, 600)}`,
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);
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}
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const data = await resp.json();
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const item = data?.data?.[0];
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if (!item) {
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throw new Error(`${kind} returned empty data[]: ${JSON.stringify(data).slice(0, 300)}`);
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}
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// OpenRouter may return either b64_json directly, a data URL, or a hosted URL.
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// For GPT-Image and Recraft, b64_json is most common.
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let dataUrl = null;
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let mime = 'image/png';
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if (item.b64_json) {
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dataUrl = `data:${mime};base64,${item.b64_json}`;
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} else if (item.url?.startsWith('data:')) {
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dataUrl = item.url;
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mime = item.url.match(/^data:([^;]+);/)?.[1] || 'image/png';
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} else if (item.url) {
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// Hosted URL — fetch and inline-base64
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const fetched = await fetch(item.url, { signal: AbortSignal.timeout(60_000) });
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if (!fetched.ok) throw new Error(`${kind} URL fetch ${fetched.status}`);
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const ct = fetched.headers.get('content-type') || 'image/png';
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mime = ct.split(';')[0].trim();
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const buf = Buffer.from(await fetched.arrayBuffer());
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dataUrl = `data:${mime};base64,${buf.toString('base64')}`;
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} else {
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throw new Error(`${kind} response has no url or b64_json`);
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}
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return { dataUrl, provider: `images_ep/${kind}`, mime };
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}
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async function callRiverflowImages({ prompt, model, aspect, imageUrls = [] }) {
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// Sourceful Riverflow lives on /api/v1/images (not chat completions).
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// Riverflow accepts up to N reference images via `image_input` /
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// `image_inputs` array depending on the upstream. We pass both keys for safety.
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const sizeMap = {
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square: '1024x1024',
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landscape: '1536x1024',
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portrait: '1024x1536',
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};
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const body = {
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model,
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prompt,
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size: sizeMap[aspect] || '1024x1024',
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n: 1,
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};
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if (imageUrls.length > 0) {
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body.image_input = imageUrls;
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body.image_inputs = imageUrls;
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}
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const resp = await fetch('https://openrouter.ai/api/v1/images', {
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method: 'POST',
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headers: {
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Authorization: `Bearer ${API_KEY}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify(body),
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signal: AbortSignal.timeout(120_000),
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});
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if (!resp.ok) {
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const errBody = await resp.text();
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throw new Error(
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`OpenRouter /api/v1/images (riverflow) ${resp.status}: ${errBody.slice(0, 600)}`,
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);
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}
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const data = await resp.json();
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const item = data?.data?.[0];
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if (!item) throw new Error('Riverflow returned empty data[]');
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if (item.b64_json) {
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return {
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dataUrl: `data:image/png;base64,${item.b64_json}`,
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provider: 'images_ep/riverflow',
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mime: 'image/png',
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};
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}
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if (item.url) {
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const fetched = await fetch(item.url, { signal: AbortSignal.timeout(60_000) });
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if (!fetched.ok) throw new Error(`Riverflow URL fetch ${fetched.status}`);
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const buf = Buffer.from(await fetched.arrayBuffer());
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return {
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dataUrl: `data:image/png;base64,${buf.toString('base64')}`,
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provider: 'images_ep/riverflow',
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mime: 'image/png',
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};
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}
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throw new Error('Riverflow response has no url or b64_json');
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}
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// ---------- Save helper ----------
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async function saveImage({ dataUrl, model, prefix }) {
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const base64 = dataUrl.replace(/^data:image\/\w+;base64,/, '');
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const bytes = Buffer.from(base64, 'base64');
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await fs.mkdir(OUTPUT_DIR, { recursive: true });
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const safeModel = model.replace(/[/:]/g, '_');
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const filename = `${prefix}-${safeModel}-${Date.now()}.png`;
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const filepath = path.join(OUTPUT_DIR, filename);
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await fs.writeFile(filepath, bytes);
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// Return Buffer under `bytes` (NOT Buffer.length) — the caller's
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// `bytes.toString('base64')` in the inline image block needs a real Buffer,
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// not a Number. `size` holds the byte length for metadata/logging.
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return { filepath, filename, bytes, size: bytes.length };
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}
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// ---------- Server instances (one per transport) ----------
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// Both instances get the same handlers — each serves one transport type.
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function registerHandlers(srv) {
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srv.setRequestHandler(ListToolsRequestSchema, async () => {
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const models = await getImageModels();
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return {
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tools: [
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{ name: 'generate_image',
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description:
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'Generate an opaque (background filled) image via OpenRouter. ' +
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'Aspect: square|landscape|portrait. ' +
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'Optional: image_urls — list of HTTP(S) or data: URLs of reference images ' +
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'(style ref, seed, i2i) — works with Gemini, GPT-Image, FLUX 2, Seedream. ' +
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'Returns {model,filepath,bytes,provider,latency_ms}. ' +
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'Use list_image_models for the full 35-model catalog.',
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inputSchema: {
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type: 'object',
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properties: {
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prompt: { type: 'string', description: 'Text prompt' },
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model: {
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type: 'string',
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enum: ['google/gemini-2.5-flash-image', 'openai/gpt-image-2', 'recraft/recraft-v3', 'black-forest-labs/flux.2-flex', 'bytedance-seed/seedream-4.5', 'openai/gpt-image-1', 'microsoft/mai-image-2.5', 'x-ai/grok-imagine-image-quality'],
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default: 'google/gemini-2.5-flash-image',
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},
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aspect: {
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type: 'string',
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enum: ['square', 'landscape', 'portrait'],
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default: 'square',
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},
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image_urls: {
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type: 'array',
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items: { type: 'string' },
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description:
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'Optional reference images. Each item is an http(s):// URL OR ' +
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'a data:image/... URL. Up to ~4 references recommended for best ' +
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'compatibility. Empty array = no refs.',
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default: [],
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},
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},
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required: ['prompt'],
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},
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},
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{
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name: 'generate_image_transparent',
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description:
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'Generate an image with a TRANSPARENT background (alpha channel PNG). ' +
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'Only works with models that support background removal natively: ' +
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'recraft/recraft-v3, openai/gpt-image-1, openai/gpt-image-1-mini, ' +
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'openai/gpt-image-2, openai/gpt-5-image, openai/gpt-5-image-mini. ' +
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'Other models will return an error from the upstream. ' +
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'Aspect: square|landscape|portrait. ' +
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'Optional image_urls — use to apply style from reference images while ' +
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'keeping transparent background.',
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inputSchema: {
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type: 'object',
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properties: {
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prompt: { type: 'string', description: 'Text prompt (mention "isolated on transparent background" for best results)' },
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model: {
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type: 'string',
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enum: TRANSPARENT_MODELS,
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default: 'recraft/recraft-v3',
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},
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aspect: {
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type: 'string',
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enum: ['square', 'landscape', 'portrait'],
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default: 'square',
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},
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image_urls: {
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type: 'array',
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items: { type: 'string' },
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description:
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'Optional reference images. Each item is an http(s):// URL OR ' +
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'a data:image/... URL. For Recraft v3: single reference. ' +
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'For GPT-Image: up to ~4 references recommended.',
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default: [],
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},
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},
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required: ['prompt'],
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},
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},
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{
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name: 'list_image_models',
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description: 'List 35 image-capable models on OpenRouter (cached 1h).',
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inputSchema: { type: 'object', properties: {} },
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},
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{
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name: 'get_image',
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description:
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'Read a previously generated image by filename. Returns multipart content: ' +
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'one inline image (base64) + one text metadata block. Use this if you want ' +
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'to re-fetch an image after a generate_image call (file persists across ' +
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|
'the same container lifetime but is lost on container restart). ' +
|
|
'Filename is the value returned in the generate_image metadata.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
filename: {
|
|
type: 'string',
|
|
description:
|
|
'Filename as returned in `filename` field from generate_image / ' +
|
|
'generate_image_transparent output (e.g. ' +
|
|
'"opaque-google_gemini-2.5-flash-image-1783615606608.png").',
|
|
},
|
|
},
|
|
required: ['filename'],
|
|
},
|
|
},
|
|
],
|
|
};
|
|
}); // end ListToolsRequestSchema
|
|
|
|
// ---- CallTool handler ----
|
|
srv.setRequestHandler(CallToolRequestSchema, async (req) => {
|
|
const { name, arguments: args } = req.params;
|
|
try {
|
|
if (name === 'list_image_models') {
|
|
const list = (await getImageModels()).join('\n');
|
|
return { content: [{ type: 'text', text: `# OpenRouter image models (${MODEL_CACHE.length})\n\n${list}` }] };
|
|
}
|
|
if (name === 'generate_image' || name === 'generate_image_transparent') {
|
|
const prompt = String(args?.prompt || '').trim();
|
|
if (!prompt) return errResp('prompt required');
|
|
const aspect = args?.aspect || 'square';
|
|
const imageUrls = normalizeImageUrls(args?.image_urls || []);
|
|
let model;
|
|
if (name === 'generate_image_transparent') {
|
|
model = args?.model || 'recraft/recraft-v3';
|
|
if (!isTransparentCapable(model))
|
|
return errResp(`Model ${model} not transparent-capable. Use: ${TRANSPARENT_MODELS.join(', ')}`);
|
|
} else {
|
|
model = args?.model || 'google/gemini-2.5-flash-image';
|
|
}
|
|
const transparent = name === 'generate_image_transparent';
|
|
if (imageUrls.length > 0 && !IMAGE_REF_MODELS.has(model))
|
|
process.stderr.write(`[gen] WARN: ${imageUrls.length} refs on model that may not support them\n`);
|
|
|
|
process.stderr.write(`[gen] req tool=${name} model=${model} aspect=${aspect} transparent=${transparent} refs=${imageUrls.length} prompt="${prompt.slice(0, 80)}"\n`);
|
|
const t0 = Date.now();
|
|
const { dataUrl, provider, mime } = await callOpenRouter({ prompt, model, aspect, transparent, imageUrls });
|
|
const { filepath, filename, bytes, size } = await saveImage({ dataUrl, model, prefix: transparent ? 'transparent' : 'opaque' });
|
|
process.stderr.write(`[gen] OK provider=${provider} mime=${mime} ${Date.now() - t0}ms ${filepath} ${size}b\n`);
|
|
|
|
return {
|
|
content: [
|
|
{ type: 'image', mimeType: mime, data: bytes.toString('base64') },
|
|
{ type: 'text', text: JSON.stringify({
|
|
tool: name, model, provider, mime, aspect, transparent,
|
|
refs_used: imageUrls.length, filepath, filename, bytes: size,
|
|
latency_ms: Date.now() - t0,
|
|
download_url: `https://img-gen-ai.dynv6.net/images/${filename}`,
|
|
}, null, 2) },
|
|
],
|
|
};
|
|
}
|
|
if (name === 'get_image') {
|
|
const filename = String(args?.filename || '').trim();
|
|
if (!filename) return errResp('filename required');
|
|
if (!/^[\w.-]+$/.test(filename)) return errResp('filename must be alphanumeric with dots/hyphens only');
|
|
const filepath = path.join(OUTPUT_DIR, filename);
|
|
let buf;
|
|
try { buf = await fs.readFile(filepath); } catch (e) { return errResp(`Image not found: ${filename}`); }
|
|
const mime = filename.endsWith('.png') ? 'image/png'
|
|
: filename.endsWith('.jpg') || filename.endsWith('.jpeg') ? 'image/jpeg'
|
|
: filename.endsWith('.webp') ? 'image/webp' : 'application/octet-stream';
|
|
process.stderr.write(`[get] OK ${filename} ${buf.length}b\n`);
|
|
return {
|
|
content: [
|
|
{ type: 'image', mimeType: mime, data: buf.toString('base64') },
|
|
{ type: 'text', text: JSON.stringify({ filename, filepath, bytes: buf.length, mime, download_url: `https://img-gen-ai.dynv6.net/images/${filename}` }, null, 2) },
|
|
],
|
|
};
|
|
}
|
|
return errResp(`Unknown tool: ${name}`);
|
|
} catch (e) {
|
|
process.stderr.write(`[gen-ERR] ${e.stack || e}\n`);
|
|
return { content: [{ type: 'text', text: `Error: ${e.message}` }], isError: true };
|
|
}
|
|
}); // end CallToolRequestSchema
|
|
} // end registerHandlers
|
|
|
|
// ---------- Create MCP server instance ----------
|
|
const mcpServer = new Server(
|
|
{ name: 'mcp-img-gen', version: '1.2.0' },
|
|
{ capabilities: { tools: {} } },
|
|
);
|
|
registerHandlers(mcpServer);
|
|
|
|
function errResp(text) {
|
|
return { content: [{ type: 'text', text }], isError: true };
|
|
}
|
|
|
|
// ---------- HTTP transport w/ Bearer auth ----------
|
|
|
|
// Traditional SSE transport sessions (for Figma / older MCP clients)
|
|
const sseSessions = new Map();
|
|
|
|
// Stateful Streamable HTTP transport (for Cursor / modern clients)
|
|
const mcpTransport = new StreamableHTTPServerTransport({
|
|
sessionIdGenerator: () => crypto.randomUUID(),
|
|
});
|
|
await mcpServer.connect(mcpTransport);
|
|
|
|
const httpServer = http.createServer(async (req, res) => {
|
|
const url = new URL(req.url, `http://${req.headers.host || 'localhost'}`);
|
|
|
|
// Auth gate — skip /health and /images/
|
|
if (!url.pathname.startsWith('/health') && !url.pathname.startsWith('/images/')) {
|
|
const auth = req.headers.authorization || '';
|
|
const expected = `Bearer ${MCP_TOKEN}`;
|
|
if (auth !== expected) {
|
|
process.stderr.write(`[auth] denied ${req.method} ${url.pathname}\n`);
|
|
res.statusCode = 401;
|
|
res.setHeader('www-authenticate', 'Bearer');
|
|
res.setHeader('content-type', 'application/json');
|
|
res.end(JSON.stringify({ error: 'invalid or missing token' }));
|
|
return;
|
|
}
|
|
}
|
|
|
|
// Lightweight /health for Coolify / Traefik probes
|
|
if (url.pathname === '/health') {
|
|
res.statusCode = 200;
|
|
res.setHeader('content-type', 'application/json');
|
|
res.end(JSON.stringify({ ok: true, version: '1.2.0', uptime: process.uptime() }));
|
|
return;
|
|
}
|
|
|
|
process.stderr.write(`[HTTP] ${req.method} ${url.pathname} -> incoming\n`);
|
|
|
|
try {
|
|
// ---- Serve saved images directly (GET /images/<filename>) ----
|
|
if (url.pathname.startsWith('/images/') && req.method === 'GET') {
|
|
const filename = url.pathname.slice('/images/'.length);
|
|
// Security: prevent path traversal
|
|
if (!filename || filename.includes('/') || filename.includes('\\') || filename.includes('..')) {
|
|
res.statusCode = 400;
|
|
res.setHeader('content-type', 'application/json');
|
|
res.end(JSON.stringify({ error: 'invalid filename' }));
|
|
return;
|
|
}
|
|
const filepath = path.join(OUTPUT_DIR, filename);
|
|
try {
|
|
const buf = await fs.readFile(filepath);
|
|
const ext = path.extname(filename).toLowerCase();
|
|
const mime = ext === '.png' ? 'image/png' : ext === '.jpg' || ext === '.jpeg' ? 'image/jpeg' : ext === '.webp' ? 'image/webp' : 'application/octet-stream';
|
|
res.statusCode = 200;
|
|
res.setHeader('content-type', mime);
|
|
res.setHeader('content-length', buf.length);
|
|
res.setHeader('cache-control', 'public, max-age=3600');
|
|
res.end(buf);
|
|
} catch (e) {
|
|
res.statusCode = 404;
|
|
res.setHeader('content-type', 'application/json');
|
|
res.end(JSON.stringify({ error: 'file not found' }));
|
|
}
|
|
process.stderr.write(`[image] GET ${filename} -> ${res.statusCode}\n`);
|
|
return;
|
|
}
|
|
|
|
// ---- Traditional SSE transport (for Figma) ----
|
|
if (url.pathname === '/sse' && req.method === 'GET') {
|
|
const sseTransport = new SSEServerTransport('/messages', res);
|
|
const sessionId = sseTransport.sessionId;
|
|
sseSessions.set(sessionId, sseTransport);
|
|
res.on('close', () => {
|
|
sseSessions.delete(sessionId);
|
|
process.stderr.write(`[sse] session ${sessionId} closed\n`);
|
|
});
|
|
// Each SSE session gets its own server instance (can't reuse mcpServer)
|
|
const sseServer = new Server(
|
|
{ name: 'mcp-img-gen', version: '1.2.0' },
|
|
{ capabilities: { tools: {} } },
|
|
);
|
|
registerHandlers(sseServer);
|
|
await sseServer.connect(sseTransport);
|
|
process.stderr.write(`[sse] session ${sessionId} established\n`);
|
|
return;
|
|
}
|
|
|
|
if (url.pathname === '/messages' && req.method === 'POST') {
|
|
const sessionId = url.searchParams.get('sessionId');
|
|
if (!sessionId || !sseSessions.has(sessionId)) {
|
|
res.statusCode = 400;
|
|
res.setHeader('content-type', 'application/json');
|
|
res.end(JSON.stringify({ error: `SSE session ${sessionId || '(missing)'} not found` }));
|
|
return;
|
|
}
|
|
const sseTransport = sseSessions.get(sessionId);
|
|
await sseTransport.handlePostMessage(req, res);
|
|
return;
|
|
}
|
|
|
|
// ---- Unified /mcp transport (Streamable HTTP) ----
|
|
// Must go last — catches any path that isn't /health /sse /messages
|
|
await mcpTransport.handleRequest(req, res);
|
|
process.stderr.write(`[mcp] ${req.method} ${url.pathname} -> ${res.statusCode}\n`);
|
|
} catch (e) {
|
|
process.stderr.write(`[HTTP-ERR] ${e.stack || e}\n`);
|
|
if (!res.headersSent) {
|
|
res.statusCode = 500;
|
|
res.setHeader('content-type', 'application/json');
|
|
res.end(JSON.stringify({ error: e.message }));
|
|
}
|
|
}
|
|
});
|
|
|
|
httpServer.listen(PORT, '0.0.0.0', () => {
|
|
process.stderr.write(`mcp-img-gen listening on http://0.0.0.0:${PORT}\n`);
|
|
});
|