Production-ready Next.js template for building AI agents with LangGraph.js. Features MCP integration for dynamic tool loading, human-in-the-loop tool approval, persistent conversation memory with PostgreSQL, and real-time streaming responses. Built with TypeScript, React, Prisma, and Tailwind CSS.
This repository also configures its own agents. See what fullstack-langgraph-nextjs-agent tells them →
agentailor/fullstack-langgraph-nextjs-agent
Skill Claude CodeCodex
Decide which AI agent behaviors are worth an eval case, then write those cases — harness-, framework-, and language-agnostic. Use when writing a first eval suite for an agent, adding cases to an existing one, reviewing eval cases or scorers someone else wrote, choosing between a deterministic check and an LLM judge…
agentailor/fullstack-langgraph-nextjs-agent
Skill Claude CodeCodex
Comprehensive guide for designing, refining, and auditing system prompts for autonomous AI agents based on Anthropic's production practices. Use when creating or refining prompts for agents that operate in loops with tool access, including when asked to write agent instructions, system prompts, agent configurations…
agentailor/fullstack-langgraph-nextjs-agent
Skill Claude CodeCodex
Design and verify tools that AI agents can actually use — for any framework or language (MCP servers, LangChain/LangGraph, function-calling, raw JSON schema; TypeScript, Python, or otherwise). Use when writing a new tool for an agent, reviewing or fixing an existing tool definition, deciding how to split capabilities…