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AI Lab Weekly — 7 Mayıs 2026 · Bu hafta Claude Code & AI'da neler oldu?
Adnan Çakmak · 2026-05-08 · via DEV Community

🇹🇷 Bu yazı, AI Lab kişisel araştırma asistanımın haftalık dijestidir. Her gün AI / Claude Code ekosistemini tarıyor; pazar günleri en iyi 6'sini burada paylaşıyorum. Hem Türkçe hem İngilizce.

🇬🇧 This is the weekly digest of my personal AI research agent. It scans the Claude Code / agentic AI ecosystem daily and surfaces the 6 most actionable findings every Sunday. Bilingual: Turkish + English.


Bu hafta öne çıkanlar / This week's picks

  1. n8n workflow'ları için Claude Code MCP sunucusu
  2. Claude Opus 4.7: agentic güvenilirlik ve kod performansında artış
  3. UI Hierarchy MCP: Next.js bileşen ağacını AI ajanlarına sunma
  4. Vibe coding ve agentic engineering birbirine yaklaşıyor
  5. Anthropic Claude Code limitlerini artırdı, SpaceX anlaşmasını açıkladı
  6. Kimlik ve Uygunluk Kontrolü için Ajan AI Mimarisi

1. n8n workflow'ları için Claude Code MCP sunucusu · n8n-MCP: Claude Code integration for n8n workflows

🇹🇷 Özet: Glama tarafından yayınlanan n8n-MCP, Claude Code ortamında n8n workflow'larını doğrudan çalıştırmayı sağlayan yeni bir MCP sunucusudur. Bu sayede Claude Code içinden n8n otomasyonlarını tetikleyip yönetebilirsin.

🇬🇧 Summary: n8n-MCP is a new MCP server released by Glama that enables running n8n workflows directly within Claude Code. It allows you to trigger and manage n8n automations directly from Claude Code.

Nasıl yapılmış / How it was built:

  1. Glama tarafından yayınlanan bu MCP sunucusu; n8n-MCP'yi Claude Code projesine entegre et
  2. MCP bağlantısını konfigüre ederek n8n instance'ına erişim sağla
  3. Claude Code içinde n8n workflow'larını çalıştırmak için API endpoint'lerini kullan
  4. n8n webhook veya REST API aracılığıyla tetikleme ve sonuç izlemeyi gerçekleştir

Araçlar / Tools: claude-code · anthropic-mcp · n8n
Zorluk / Difficulty: Orta · Uygulanabilirlik / Applicability: Hemen denenebilir
Kaynak / Source: Glama MCP (yeni server'lar)


2. Claude Opus 4.7: agentic güvenilirlik ve kod performansında artış · Claude Opus 4.7: agentic reliability and improved coding performance

🇹🇷 Özet: Anthropic, Opus 4.7'yi yayınladı. SWE-Bench Verified'de %87.6'ya ulaşan en güçlü coding performansı, tool-call başına daha yüksek kalite oranı ve daha az döngü problemi sunuyor. Yeni xhigh effort level, Task Budgets ve /ultrareview özellikleri ajan işleri için güvenilirliği artırıyor; API fiyatlandırması Opus 4.6 ile aynı.

🇬🇧 Summary: Anthropic launched Opus 4.7 with the strongest coding performance of any available frontier model (87.6% on SWE-Bench Verified), higher quality-per-tool-call ratio, and fewer looping issues. New features like xhigh effort level, Task Budgets, and /ultrareview enhance agent reliability for autonomous workflows; pricing remains identical to Opus 4.6.

Nasıl yapılmış / How it was built:

  1. Claude API'de model='claude-opus-4-7' seçerek kullan
  2. Claude Code'da xhigh effort level varsayılan olarak ayarlanmış; high/max arasında daha etkin kimlik kullan
  3. Task Budgets (beta) ile uzun multi-step işlerde token harcamasını sınırla ve modelin öncelik vermesini sağla
  4. Pro/Max hesapla /ultrareview kod review oturumunu test et (her ay 3 free)
  5. Opus 4.6'deki promptlar genelde çalışır ama katı instruction-following için fine-tuning gerekebilir
  6. Amazon Bedrock, Google Vertex AI veya Microsoft Foundry üzerinden de erişilebilir

Araçlar / Tools: claude-api · anthropic-sdk · claude-code · amazon-bedrock · google-vertex-ai
Zorluk / Difficulty: Kolay · Uygulanabilirlik / Applicability: Hemen denenebilir
Kaynak / Source: dev.to - Claude


3. UI Hierarchy MCP: Next.js bileşen ağacını AI ajanlarına sunma · UI Hierarchy MCP: Expose Next.js component tree to AI agents

🇹🇷 Özet: Next.js App Router projelerini parse edip UI bileşen hiyerarşisini yapılandırılmış çıktı (markdown ağaç + JSON) olarak sunan MCP sunucusu. AI kod ajanları ekran görüntüsü veya belirsiz açıklamaya güvenli bir şekilde yanıt veremediğinde, bu MCP'yi çağırarak dosya/satır, layout ipuçları, metin içeriği ve koşullu dallar içeren kesin bileşen haritası alabilir.

🇬🇧 Summary: An MCP server that parses Next.js App Router projects and returns the UI component hierarchy as structured output (markdown tree + JSON). When AI coding agents cannot confidently act on a screenshot or vague description, they can call this MCP to get a precise component map with file:line, layout hints, text content, and conditional branches.

Nasıl yapılmış / How it was built:

  1. Next.js App Router projesini statik analiz et (dosya ve bileşen yapısı)
  2. Bileşen ağacını traverse et; her bileşen için dosya yolu, satır numarası, props, metin içeriği ve koşullu render koşullarını kaydet
  3. Yapılandırılmış çıktıyı iki formatta sun: markdown ağaç (okunabilirlik) ve JSON (AI parsing)
  4. MCP protokolü ile bu server'ı Claude Code veya diğer ajanlar tarafından çağrılabilir hale getir
  5. AI ajan, screenshot veya belirsiz talep aldığında exact dosya/satır bilgisini kullanarak hedefli düzenleme yap

Araçlar / Tools: mcp · next-js · node-js
Zorluk / Difficulty: Ileri · Uygulanabilirlik / Applicability: Hemen denenebilir
Kaynak / Source: r/mcp


4. Vibe coding ve agentic engineering birbirine yaklaşıyor · Vibe coding and agentic engineering are converging

🇹🇷 Özet: Simon Willison, AI kod yazma araçlarında vibe coding (kodun kalitesine aldırmadan AI'dan istediğini alma) ile agentic engineering (sorumlu AI kullanımı) arasındaki farkın kendi çalışmasında bulanıklaştığını fark etti. Bu iki yaklaşımın tam olarak ayrı olmadığını ve birleşmeye başladığını tartışıyor.

🇬🇧 Summary: Simon Willison realizes that vibe coding—asking AI for code without caring about quality—and agentic engineering, a more responsible AI coding approach, are blurring together in his own work. He discusses how the two approaches are converging rather than remaining distinct.

Nasıl yapılmış / How it was built:

  1. Bu bir yazı ve podcast görüşmesinden türetilen fikir. Ayrıntılı uygulama adımı yok, Simon Willison'ın vibe coding ve agentic engineering konseptleri hakkında düşüncelerini paylaştığı bir makaledir.

Araçlar / Tools: claude-code · ai-coding-tools
Zorluk / Difficulty: Kolay · Uygulanabilirlik / Applicability: Fikir aşaması
Kaynak / Source: Simon Willison (LLM ekosistemi)


5. Anthropic Claude Code limitlerini artırdı, SpaceX anlaşmasını açıkladı · Anthropic raises Claude Code usage limits, announces SpaceX partnership

🇹🇷 Özet: Anthropic Claude Code'un kullanım limitlerini yükselterek daha fazla kod yürütme imkanı sunuyor. SpaceX ile yeni bir ortaklık anlaşması da açıklandı; bu anlaşmanın detayları henüz tam netleştirilmemiş olup, artan limitler tüm kullanıcılar için geçerli olacak.

🇬🇧 Summary: Anthropic has increased Claude Code usage limits, enabling more code executions for users. A new partnership deal with SpaceX was also announced, though specific details remain unclear. The raised limits will apply to all users.

Nasıl yapılmış / How it was built:

  1. Bu bir ürün duyurusu ve iş ortaklığı haberidir; teknik uygulama adımı yok
  2. Mevcut Claude Code kullanıcıları yeni yüksek limitlerden otomatik olarak faydalanacak

Araçlar / Tools: claude-code · anthropic-api
Zorluk / Difficulty: Kolay · Uygulanabilirlik / Applicability: Fikir aşaması
Kaynak / Source: Hacker News - AI


6. Kimlik ve Uygunluk Kontrolü için Ajan AI Mimarisi · Architectural Framework for Agentic AI in Identity and Eligibility

🇹🇷 Özet: Microsoft, kimlik doğrulama ve uygunluk kontrolü işlemlerini otomatikleştirmek için bir ajan AI mimarisi sunuyor. Framework, kamu kurumlarında yaygın olan sıkça tekrarlanan kontrol görevlerini yapay zeka ajanları ile çalıştırabilir hale getiriyor.

🇬🇧 Summary: Microsoft presents an architectural framework for agentic AI designed to automate identity verification and eligibility checks. The framework enables government agencies to run repetitive compliance and eligibility tasks through AI agents.

Nasıl yapılmış / How it was built:

  1. Bu kaynak bir whitepaper/mimarı rehberi olup, uygulama adımları teknik detay olarak tam verilmemiş; makalede önerilen framework'ün genel tasarım ilkeleri açıklanmıştır.

Araçlar / Tools: agentic-ai · identity-verification
Zorluk / Difficulty: Ileri · Uygulanabilirlik / Applicability: Fikir aşaması
Kaynak / Source: Hacker News - AI


Otomatik üretildi: AI Lab · hafta 2026-W19 · 6 içerik · TR/EN paralel.