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kennethkutynkennethkutyn
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adding MCP
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‎proxy/env.example‎

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@@ -11,4 +11,6 @@ DATABASE_URL=postgresql://user:password@host:port/dbname
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JWT_SECRET=
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# Google OAuth Client ID (from Google Cloud Console)
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GOOGLE_CLIENT_ID=
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# Frontend URL used by MCP to generate diagram links
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FRONTEND_BASE_URL=https://kennethkutyn.github.io/AmpliStack
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‎proxy/index.js‎

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@@ -6,6 +6,7 @@ import cors from 'cors';
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import express from 'express';
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import OpenAI from 'openai';
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import pg from 'pg';
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import { mountMcp } from './mcp.js';
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const __dirname = path.dirname(fileURLToPath(import.meta.url));
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loadEnv({ path: path.join(__dirname, '.env') });
@@ -477,6 +478,10 @@ app.post('/api/diagrams/:shortCode/fork', authMiddleware(true), async (req, res)
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}
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});
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// --- MCP server ---
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const FRONTEND_BASE_URL = process.env.FRONTEND_BASE_URL || 'https://kennethkutyn.github.io/AmpliStack';
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mountMcp(app, { openai, openaiModel: OPENAI_MODEL, baseUrl: FRONTEND_BASE_URL });
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// --- Start server ---
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(async () => {
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await initDb();

‎proxy/mcp.js‎

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import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
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import { StreamableHTTPServerTransport } from '@modelcontextprotocol/sdk/server/streamableHttp.js';
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import { z } from 'zod';
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import { promisify } from 'util';
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import { gzip } from 'zlib';
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const gzipAsync = promisify(gzip);
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// Mirror of the known item catalog from the frontend config.js
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const KNOWN_ITEMS = {
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'paid-ads': 'marketing', 'email': 'marketing', 'sms': 'marketing',
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'push-notifications': 'marketing', 'social-media': 'marketing',
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'search': 'marketing', 'referral': 'marketing',
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'website': 'experiences', 'web-app': 'experiences', 'mobile-app': 'experiences',
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'ott': 'experiences', 'call-center': 'experiences', 'pos': 'experiences',
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'amplitude-sdk': 'sources', 'segment': 'sources', 'tealium': 'sources',
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'api': 'sources', 'cdp': 'sources', 'etl': 'sources', 'crm': 'sources',
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'amplitude-analytics': 'analysis', 'snowflake': 'analysis', 'bigquery': 'analysis',
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'databricks': 'analysis', 'bi': 'analysis', 's3': 'analysis', 'llm': 'analysis',
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'amp-gs': 'activation', 'amp-webexp': 'activation', 'amp-feaexp': 'activation',
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'amp-assistant': 'activation', 'braze': 'activation', 'iterable': 'activation',
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'salesforce': 'activation', 'hubspot': 'activation', 'marketo': 'activation',
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'intercom': 'activation'
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};
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const VALID_LAYERS = new Set(['marketing', 'experiences', 'sources', 'analysis', 'activation']);
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function slugify(value) {
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return (value || '').toString().trim().toLowerCase()
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.replace(/[^a-z0-9]+/g, '-').replace(/^-+|-+$/g, '') || 'node';
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}
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function guessLayerFromKind(kind) {
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const lower = (kind || '').toString().trim().toLowerCase();
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if (!lower) return null;
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if (lower === 'activation') return 'activation';
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if (lower === 'warehouse' || lower === 'analysis') return 'analysis';
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if (lower === 'amplitude') return 'analysis';
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if (lower === 'datasource' || lower === 'source') return 'sources';
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return null;
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}
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function buildConnectionKey(sourceId, targetId) {
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return [sourceId, targetId].sort().join('::');
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}
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/**
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* Build a serialized diagram state from the AI response (mirrors frontend applyDiagramFromAi).
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*/
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function buildDiagramState(aiResult, title) {
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const nodes = Array.isArray(aiResult.diagramNodes) ? aiResult.diagramNodes : [];
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const edges = Array.isArray(aiResult.diagramEdges) ? aiResult.diagramEdges : [];
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const addedItems = { marketing: [], experiences: [], sources: [], analysis: [], activation: [] };
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const customEntries = { marketing: [], experiences: [], sources: [], analysis: [], activation: [] };
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const layerOrder = { marketing: [], experiences: [], sources: [], analysis: [], activation: [] };
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const customConnections = [];
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const itemCategoryIndex = { ...KNOWN_ITEMS };
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for (const node of nodes) {
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const id = node?.id || slugify(node?.label);
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const label = node?.label || id;
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const rawLayer = (node?.layer || '').toString().trim().toLowerCase();
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const normalizedLayer = VALID_LAYERS.has(rawLayer) ? rawLayer : null;
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const kindLayer = guessLayerFromKind(node?.kind);
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// Known catalog item
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if (KNOWN_ITEMS[id]) {
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const category = KNOWN_ITEMS[id];
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if (!addedItems[category].includes(id)) {
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addedItems[category].push(id);
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layerOrder[category].push(id);
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}
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continue;
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}
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// Custom item — resolve layer
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const category = normalizedLayer || kindLayer || 'analysis';
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itemCategoryIndex[id] = category;
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if (!customEntries[category].some(e => e.id === id)) {
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customEntries[category].push({ id, name: label, icon: 'custom', isCustom: true });
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}
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if (!addedItems[category].includes(id)) {
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addedItems[category].push(id);
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layerOrder[category].push(id);
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}
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}
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for (const edge of edges) {
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const sourceId = edge?.sourceId;
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const targetId = edge?.targetId;
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if (!sourceId || !targetId) continue;
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if (!itemCategoryIndex[sourceId] || !itemCategoryIndex[targetId]) continue;
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const key = buildConnectionKey(sourceId, targetId);
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if (!customConnections.includes(key)) {
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customConnections.push(key);
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}
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}
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return {
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version: 1,
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activeCategory: 'marketing',
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activeModel: null,
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diagramTitle: title || 'MCP-generated Diagram',
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lastEditedAt: new Date().toISOString(),
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addedItems,
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customEntries,
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layerOrder,
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customConnections,
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dismissedConnections: [],
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dottedConnections: [],
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connectionAnnotations: {},
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amplitudeSdkSelectedBadges: [],
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nodeNotes: {}
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};
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}
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async function encodeStateForUrl(state) {
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const json = JSON.stringify(state);
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const compressed = await gzipAsync(Buffer.from(json, 'utf8'));
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// base64url encode
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return compressed.toString('base64url');
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}
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const SYSTEM_PROMPT = `
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You are an Amplitude analytics solutions architect. Given a call transcript, extract architecture-ready details for building a data/activation diagram.
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Return ONLY valid JSON with this shape:
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{
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"architecture": { "goal": string, "scope": string },
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"events": [
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{ "name": string, "properties": [string], "notes": string }
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],
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"risks": [string],
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"assumptions": [string],
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"diagramNodes": [
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{ "id": string, "label": string, "layer": "marketing|experiences|sources|analysis|activation", "kind": "amplitude|warehouse|activation|custom", "notes": string }
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],
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"diagramEdges": [
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{ "sourceId": string, "targetId": string, "label": string }
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]
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}
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Rules:
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- JSON only; no prose.
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- Use best-effort extraction even if partial.
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- If there is mention of web site, web app, or mobile app, make sure to add an appropriate node to the "owned experiences" layer.
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- if they mention a service or vendor that doesn't exist, you can suggest a new node and guess the most appropriate layer.
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- Pay special attention to mention of Amplitude SDK. If they mention Mobile or Web app, assume an AMplitude SDK will be present unless the specifically say otherwise or mention a CDP.
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- Prefer concise labels; derive stable ids from names (lowercase, dashes).
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- Map AmpliStack layers: marketing, experiences (owned surfaces/apps), sources (ingest), analysis (warehouse/BI/Amplitude), activation (destinations/engagement).
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- For diagramEdges, keep labels descriptive (e.g., "track events", "sync audiences").
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- If there is a mention of push, email, ads or similar, make sure to add the appropriate node to the "marketing channesl" layer
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- If something is unknown, use an empty array or empty string rather than guessing.
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`;
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/**
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* Mount MCP Streamable HTTP endpoints on an existing Express app.
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*/
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export function mountMcp(app, { openai, openaiModel, baseUrl }) {
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// Stateless: create a fresh server+transport per request
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function createServer() {
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const server = new McpServer({
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name: 'amplistack',
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version: '1.0.0'
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});
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server.registerTool(
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'create_diagram',
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{
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title: 'Create Diagram',
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description: 'Generate an Amplistack architecture diagram from a text description. Returns a link to the interactive diagram.',
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inputSchema: { description: z.string().describe('A text description of the architecture, customer setup, or call transcript to turn into a diagram') }
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},
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async ({ description }) => {
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if (!openai) {
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return { content: [{ type: 'text', text: 'Error: OpenAI API key not configured on server.' }] };
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}
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// 1. Call OpenAI
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const completion = await openai.chat.completions.create({
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model: openaiModel,
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messages: [
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{ role: 'system', content: SYSTEM_PROMPT },
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{ role: 'user', content: `Transcript:\n${description}` }
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],
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response_format: { type: 'json_object' },
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temperature: 0.2
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});
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const content = completion.choices?.[0]?.message?.content;
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if (!content) {
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return { content: [{ type: 'text', text: 'Error: Empty response from AI model.' }] };
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}
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let aiResult;
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try { aiResult = JSON.parse(content); }
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catch { return { content: [{ type: 'text', text: 'Error: Failed to parse AI response as JSON.' }] }; }
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// 2. Build diagram state
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const state = buildDiagramState(aiResult, 'AI-generated Diagram');
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// 3. Encode as URL
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const encoded = await encodeStateForUrl(state);
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const diagramUrl = `${baseUrl}/?state=${encoded}`;
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// 4. Build summary
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const nodeCount = (aiResult.diagramNodes || []).length;
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const edgeCount = (aiResult.diagramEdges || []).length;
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const goal = aiResult.architecture?.goal || '';
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const layers = [...new Set((aiResult.diagramNodes || []).map(n => n.layer).filter(Boolean))];
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const summary = [
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`Diagram created with ${nodeCount} nodes and ${edgeCount} connections.`,
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goal ? `\nGoal: ${goal}` : '',
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layers.length ? `\nLayers used: ${layers.join(', ')}` : '',
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`\nView diagram: ${diagramUrl}`
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].join('');
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return {
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content: [
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{ type: 'text', text: summary }
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]
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};
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}
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);
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return server;
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}
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// POST /mcp — main MCP endpoint (stateless)
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app.post('/mcp', async (req, res) => {
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try {
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const transport = new StreamableHTTPServerTransport({ sessionIdGenerator: undefined });
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const server = createServer();
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await server.connect(transport);
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await transport.handleRequest(req, res, req.body);
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} catch (error) {
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console.error('MCP request error:', error);
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if (!res.headersSent) {
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res.status(500).json({ jsonrpc: '2.0', error: { code: -32603, message: 'Internal server error' }, id: null });
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}
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}
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});
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// GET /mcp and DELETE /mcp — not supported in stateless mode
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app.get('/mcp', (req, res) => {
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res.status(405).json({ jsonrpc: '2.0', error: { code: -32000, message: 'SSE not supported in stateless mode. Use POST.' }, id: null });
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});
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app.delete('/mcp', (req, res) => {
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res.status(405).json({ jsonrpc: '2.0', error: { code: -32000, message: 'Session management not supported in stateless mode.' }, id: null });
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});
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console.log('MCP server mounted at /mcp (Streamable HTTP, stateless)');
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}

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