Map the ecosystem, score your stack, compare head-to-head. Built for engineers who ship.
A solid prompt gets you 80% there — rejection reasoning, tradeoffs, kill conditions. We know. So we wrote the prompt. Take it. Use it.
You are a senior AI engineer helping me evaluate my tech stack. I'm building: [describe your product in 1–2 sentences] My team: [solo / 2–5 / 10+ engineers] Stage: [prototype / early users / scaling] Budget: [bootstrapped / seed / Series A+] OSS preference: [prefer open source / commercial is fine / indifferent] For each tool I list below, tell me: • Why it's the right choice for my context • The top 2 alternatives I rejected — and what signal would make me switch • Known failure modes / when I should replace it (kill conditions) • What "graduating" from this tool looks like at 10× scale My current stack: • Code Editor: [e.g. Cursor] • LLM API: [e.g. Claude API] • Agent Framework: [e.g. LangGraph] • Vector DB: [e.g. Pgvector] • Observability: [e.g. Langfuse] • Eval Layer: [e.g. none yet] • Deployment: [e.g. Vercel] Also: flag any critical gaps — tool categories I haven't covered that I probably should. Format as a structured decision brief I can share with my team.
Here's the other 20%.
Not a directory. A decision tool.
Every stack tells you what was considered and explicitly ruled out — and why. No other tool in this space does this.
Each stack defines exactly when it stops being the right choice. Know your exit before you're stuck.
When you hit a kill condition, the next stack is already mapped. Your progression arc is visible from the start.
25 stacks organized across 5 decision clusters
Paste your package.json or requirements.txtand get a fitness score for your AI stack — which slots are covered, which are missing, and where you're leaving performance on the table.
No eval layer. You're shipping vibes to production.
25 stacks with rejection reasoning
Each stack lists what was considered and rejected — and why. Plus kill conditions for when to move on and where to graduate next.
Explore the full AI ecosystem
Map 207 tools across 17 categories. Browse relationships, filter by category, and explore in 2D or 3D.
Design your own stack
Pick one tool per slot and watch your stack wire together. Share it with a single URL.
Side-by-side tool analysis
Pick any two tools and see pricing, type, GitHub stars, shared connections, and unique integrations in one view.
Is your stack production-ready?
Paste your package.json or requirements.txt and get a fitness score, slot coverage analysis, and an adversarial challenge of every tool choice.
MCP Server
AIchitect already scored 207 tools, ranked 25 curated stacks, and tracks live health signals. Add it as a remote MCP server and get structured recommendations in one call — no token-burning ecosystem research needed.
aichitect.dev/api/mcpAIchitect is fully open source. Browse the code, open issues, suggest tools, or contribute new stacks. The more the merrier.
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