feat(mcps): add kabelfachmann MCP with Kabelhandbuch integration and remove legacy PM2 orchestration
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@@ -1,75 +1,108 @@
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import { PayloadRequest } from 'payload'
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import { PayloadRequest } from "payload";
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import { parseMarkdownToLexical } from "../utils/lexicalParser.js";
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export const optimizePostEndpoint = async (req: PayloadRequest) => {
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try {
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let body: any = {};
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try {
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const { draftContent, instructions } = (await req.json?.() || {}) as { draftContent: string; instructions?: string };
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if (!draftContent) {
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return Response.json({ error: 'Missing draftContent' }, { status: 400 })
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}
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const globalAiSettings = (await req.payload.findGlobal({ slug: "ai-settings" })) as any;
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const customSources =
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globalAiSettings?.customSources?.map((s: any) => s.sourceName) || [];
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const OPENROUTER_KEY =
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process.env.OPENROUTER_KEY || process.env.OPENROUTER_API_KEY;
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const REPLICATE_KEY = process.env.REPLICATE_API_KEY;
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if (!OPENROUTER_KEY) {
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return Response.json({ error: "OPENROUTER_KEY not found in environment." }, { status: 500 })
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}
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// Dynamically import to avoid bundling it into client components that might accidentally import this file
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const importDynamic = new Function("modulePath", "return import(modulePath)");
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const { AiBlogPostOrchestrator } = await importDynamic("@mintel/content-engine");
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const orchestrator = new AiBlogPostOrchestrator({
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apiKey: OPENROUTER_KEY,
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replicateApiKey: REPLICATE_KEY,
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model: "google/gemini-3-flash-preview",
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});
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const contextDocsData = await req.payload.find({
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collection: "context-files" as any,
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limit: 100,
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});
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const projectContext = contextDocsData.docs.map((doc: any) => doc.content);
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const optimizedMarkdown = await orchestrator.optimizeDocument({
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content: draftContent,
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projectContext,
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availableComponents: [],
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instructions,
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internalLinks: [],
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customSources,
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});
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if (!optimizedMarkdown || typeof optimizedMarkdown !== "string") {
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return Response.json({ error: "AI returned invalid markup." }, { status: 500 })
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}
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const blocks = parseMarkdownToLexical(optimizedMarkdown);
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return Response.json({
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success: true,
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lexicalAST: {
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root: {
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type: "root",
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format: "",
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indent: 0,
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version: 1,
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children: blocks,
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direction: "ltr",
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},
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},
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})
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} catch (error: any) {
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console.error("Failed to optimize post in endpoint:", error);
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return Response.json({
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success: false,
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error: error.message || "An unknown error occurred during optimization.",
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}, { status: 500 })
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if (req.body) {
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// req.json() acts as a method in Next.js/Payload req wrapper
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body = (await req.json?.()) || {};
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}
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} catch (e) {
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// Ignore JSON parse error, body remains empty
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}
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}
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const { draftContent, instructions } = body as {
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draftContent?: string;
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instructions?: string;
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};
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if (!draftContent) {
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return Response.json(
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{ success: false, error: "Missing draftContent" },
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{ status: 400 },
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);
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}
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const globalAiSettings = (await req.payload.findGlobal({
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slug: "ai-settings",
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})) as any;
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const customSources =
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globalAiSettings?.customSources?.map((s: any) => s.sourceName) || [];
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const OPENROUTER_KEY =
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process.env.OPENROUTER_KEY || process.env.OPENROUTER_API_KEY;
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const REPLICATE_KEY = process.env.REPLICATE_API_KEY;
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if (!OPENROUTER_KEY) {
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return Response.json(
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{ error: "OPENROUTER_KEY not found in environment." },
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{ status: 500 },
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);
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}
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// Dynamically import to avoid bundling it into client components that might accidentally import this file
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const importDynamic = new Function(
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"modulePath",
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"return import(modulePath)",
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);
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const { AiBlogPostOrchestrator } = await importDynamic(
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"@mintel/content-engine",
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);
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const orchestrator = new AiBlogPostOrchestrator({
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apiKey: OPENROUTER_KEY,
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replicateApiKey: REPLICATE_KEY,
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model: "google/gemini-3-flash-preview",
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});
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const contextDocsData = await req.payload.find({
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collection: "context-files" as any,
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limit: 100,
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});
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const projectContext = contextDocsData.docs.map((doc: any) => doc.content);
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const optimizedMarkdown = await orchestrator.optimizeDocument({
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content: draftContent,
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projectContext,
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availableComponents: [],
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instructions,
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internalLinks: [],
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customSources,
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});
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if (!optimizedMarkdown || typeof optimizedMarkdown !== "string") {
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return Response.json(
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{ error: "AI returned invalid markup." },
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{ status: 500 },
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);
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}
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const blocks = parseMarkdownToLexical(optimizedMarkdown);
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return Response.json({
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success: true,
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lexicalAST: {
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root: {
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type: "root",
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format: "",
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indent: 0,
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version: 1,
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children: blocks,
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direction: "ltr",
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},
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},
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});
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} catch (error: any) {
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console.error("Failed to optimize post in endpoint:", error);
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return Response.json(
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{
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success: false,
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error:
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error.message || "An unknown error occurred during optimization.",
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},
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{ status: 500 },
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);
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}
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};
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