aws-agentcore-langgraph

aws-agentcore-langgraph extends your AI assistant with the ability to deploy production LangGraph agents on AWS Bedrock AgentCore. Use for (1) multi-agent systems with orchestrator and specialist agent patterns, (2) building stateful agents with persistent cross-session memory, (3) connecting external tools via AgentCore Gateway (MCP, Lambda, APIs), (4) managing shared context across distributed agents, or (5) deploying complex agent ecosystems via CLI with production observability and scaling. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly — and it will take care of the task end-to-end, using aws-agentcore-langgraph as its underlying capability.

aws-agentcore-langgraph works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) — an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install aws-agentcore-langgraph once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.

aws-agentcore-langgraph installs like any other MCP skill: drop the folder into `~/.claude/skills/aws-agentcore-langgraph/` for global access, or `.claude/skills/aws-agentcore-langgraph/` to keep it scoped to one project. After a quick restart of Claude, you can trigger it explicitly with `/aws-agentcore-langgraph`, or let the AI decide when it's the right tool for your request.

aws-agentcore-langgraph has been installed 1,535 times, making it one of the more actively used skills in the Developer & DevOps category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.