How does context injection improve the AI response?

By capturing page metadata and user info on the frontend and injecting it into the backend prompt, the AI gains immediate situational awareness without the user needing to provide background info.

How are MCP tools authenticated?

The skill demonstrates how to pass credentials through system prompts to ensure MCP tools can securely access user-specific data during agent execution.

Can I use this with Next.js applications?

Yes, it includes specific patterns for Next.js, including handling httpOnly cookies through server-side proxies and optimized script loading strategies.

Does it support database persistence?

Yes, it provides patterns for using SQLModel and SQLAlchemy to store conversation threads and message history in PostgreSQL or other relational databases.

AI Chat Interface Builder

Name: AI Chat Interface Builder
Author: Asmayaseen

byAsmayaseen

API Development

Builds production-grade AI chat interfaces with custom backend integration, secure authentication, and granular context injection.

About

This skill provides comprehensive patterns for architecting professional AI chat experiences using ChatKit and custom agents. It covers critical implementation details including streaming backend servers, secure JWT and httpOnly cookie authentication for Next.js, and persistent database storage. Developers can leverage advanced patterns for injecting user and page-level context into LLM prompts, ensuring agents have the necessary background info to provide relevant, personalized responses while maintaining secure MCP tool access.

Key Features

Database persistence patterns using SQLModel and SQLAlchemy
0 GitHub stars
Custom backend integration with ChatKitServer and Python agents
Automated page and user context injection for frontend applications
Secure authentication patterns for JWT, JWKS, and httpOnly cookies
Next.js optimized script loading and API proxying strategies

Use Cases

Building a context-aware support bot integrated into a SaaS dashboard
Creating interactive chat widgets that persist state across user sessions
Implementing secure internal AI tools with enterprise authentication

About

Key Features

Database persistence patterns using SQLModel and SQLAlchemy
0 GitHub stars
Custom backend integration with ChatKitServer and Python agents
Automated page and user context injection for frontend applications
Secure authentication patterns for JWT, JWKS, and httpOnly cookies
Next.js optimized script loading and API proxying strategies

Use Cases

Building a context-aware support bot integrated into a SaaS dashboard
Creating interactive chat widgets that persist state across user sessions
Implementing secure internal AI tools with enterprise authentication