Create AI Agents in a No-Code Visual Builder or TypeScript SDK with full 2-way sync. For shipping AI assistants and multi-agent AI workflows.

AI assistant integration for n8n workflow automation through Model Context Protocol (MCP). Connect Claude Desktop, ChatGPT, and other AI assistants to n8n for natural language workflow management.

Trigger.dev – build and deploy fully‑managed AI agents and workflows

A comprehensive Model Context Protocol (MCP) server that enables AI assistants to control Unreal Engine through the native C++ Automation Bridge plugin. Built with TypeScript and C++.

A MCP for Claude Desktop / Claude Code / Windsurf / Cursor to build n8n workflows for you

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

Run your Calaf recruiting book from chat: firms, people, pipeline, calendar, notes, and prep.

Build AI agents that actually do things. Synapse is an open-source platform for creating, connecting, and orchestrating AI agents powered by any LLM — local, cloud or CLIs.

Infrastructure that connects LLMs to ERPNext. Frappe Assistant Core works with the Model Context Protocol (MCP) to expose ERPNext functionality to any compatible Language Model

InnoShop is an AI-powered open source e-commerce system built on Laravel 13. It supports multiple AI models and native MCP (Model Context Protocol) for intelligent automation, with multi-language and multi-currency out of the box. Modular architecture and flexible plugin/theme system make it highly adaptable to diverse business needs.

MCP servers for the UniFi suite of applications, Network, Protect, Access, and Drive

Where specs become law. A self-contained MCP suite that turns any repo into a spec-driven, agent-ready project: its own constitution (foundation), its own local code graph (Compass), its own spec-driven workflow (Lawbook), and opt-in skill packs (Tools).

🚀 Universal SDK for building next-gen MCP servers

🌋 Build AI agents that seamlessly combine LLM reasoning with real-world actions via MCP tools — in just a few lines of TypeScript.