Claude Code: How to Connect Your AI-Built Frontend to a Real Backend

If you've built a frontend with Claude Code, you know the wall: it looks great but runs on hardcoded data — no database, no auth, no real API calls. Here are the four integration options, ordered from most granular to highest abstraction:
1. Raw HTTP APIs
The most granular option. Think of it like buying individual pages from a bookstore — one request, one response. Maximum control, maximum setup work. Every integration starts here under the hood. You craft specific HTTP calls to your backend endpoints.
2. SDKs (Software Development Kits)
Pre-packaged wrappers around APIs. Instead of assembling raw HTTP calls, someone gives you a library with clean functions like supabase.auth.signUp(). Way less boilerplate, way fewer mistakes. Common examples: Supabase, Stripe, Firebase — all ship SDKs that Claude Code can use directly.
3. CLIs
Best for deployment and infrastructure tasks. These aren't for runtime app calls — you use them to push code live, create database tables, and set up environments. Claude Code can run CLIs for you during development/deplyment.
4. MCP (Model Context Protocol)
The newest option. It lets Claude Code connect directly to external services as tools. Instead of writing integration code, Claude just calls the service natively. Ideal for rapid prototyping where you want to skip manual integration code entirely.
For a step-by-step tutorial, check the Reddit source link below.
📖 Read the full source: r/ClaudeAI
👀 See Also

Krasis: Hybrid CPU/GPU Runtime for Large MoE Models Achieves 3,324 tok/s Prefill on RTX 5080
Krasis is a hybrid CPU/GPU runtime that runs large MoE models by handling prefill on GPU and decode on CPU, achieving 3,324 tokens/second prefill on an RTX 5080 with Qwen3-Coder-Next 80B Q4. It requires ~2.5x model size in system RAM but enables running models too large for VRAM.

Setting Up OpenClaw as an Always-On AI Assistant
OpenClaw, configured as an always-on AI assistant for a small dev team, is set up on a Railway server with Claude as the backend and integrates with Google Workspace, GitHub, and more.

Framework for AI Teammates in Slack, Operated Entirely from Claude Code
ginnie-agents is an open-source framework for running autonomous AI agents with Slack identities, three-tier memory, cron routines, and work hours — all configured and operated through Claude Code. Requires Claude Code Max, Docker, Node 22+, and a Slack workspace with app creation permissions.

Reddit user experiments with failure-learning coding agents to break retry loops
A developer on r/LocalLLaMA describes experimenting with coding agents that learn from failures by storing simplified root causes and matching fixes, reducing repetitive error loops.