Tag: #aws
20 packages • ⭐ 17,890 total stars
Official MCP Servers for AWS
Open-source, self-hosted CMS platform on AWS serverless (Lambda, DynamoDB, S3). TypeScript framework with multi-tenancy, lifecycle hooks, GraphQL API, and AI-assisted development via MCP server. Built
Sandboxed code execution for AI agents, locally or on the cloud. Massively parallel, easy to extend. Powering SWE-agent and more.
High-fidelity, anycloud emulators running in your laptop. For DevOps programming, testing, and simulation.
Learn to build AI agents with Strands framework. Covers LLM integration via Amazon Bedrock/Anthropic, AWS service connections, tool implementation with MCP/A2A protocols, and agent evaluation using La
The @aws/nx-plugin is a collection of code generators that automate the creation and configuration of cloud-native applications using AWS, TypeScript, Python and React within the Nx development ecosys
🦾 A production‑ready research outreach AI agent that plans, discovers, reasons, uses tools, auto‑builds cited briefings, and drafts tailored emails with tool‑chaining, memory, tests, and turnkey Dock
A multi-agent AI architecture that connects 25+ specialized agents through n8n and MCP servers. Project NOVA routes requests to domain-specific experts, enabling control of applications from knowledge
Official ServerlessClaw: The authoritative autonomous AI agent swarm for AWS. Zero idle cost, self-evolving, and infinite scale. Powered by OpenClaw.
🤖 Develop enterprise AI agents with integrated tools for chat, video, image editing, and secure multi-tenant workflows.
Provide free, open access to comprehensive AI tools, guides, reviews, and resources to reduce knowledge gaps and empower users.
🤖 Implement hybrid human-AI orchestration patterns in Python to coordinate agents, manage sessions, and enable smooth AI-human handoffs.
🔧 Expose Hono API endpoints as MCP tools, simplifying integration and enhancing your API's functionality.
🛠️ Streamline your development with Kiro, an agentic IDE that transforms prototypes into production using spec-driven methods and AI-powered coding support.
🌟 Track token consumption in real-time with MCP Audit. Diagnose context bloat and unexpected spikes across MCP servers and tools efficiently.
🔍 Build a production-ready RAG system that combines LangGraph and MCP integration for precise, context-aware AI-driven question answering.
🛠️ Accelerate your Python and JavaScript development with Claude Kit's toolkit, featuring specialized agents, slash commands, and advanced context management.
🚀 Process JSON data in batches with `llm-batch`, leveraging sequential or parallel modes for efficient interaction with LLMs.
Generate reliable short finance explainer videos with script, slides, voice, subtitles, and batch-ready rendering in a stable, modular workflow.