Awesome AI Agents › Low-Code/No-Code Platforms
Heym is an AI-native automation platform built around language models, agents and tooling rather than around classic trigger-action automation with AI added later. Workflows are assembled on a visual canvas that wires together agent nodes, LLM nodes, vector stores, web scrapers, HTTP calls and message queues, and the same workflow can also be produced from a natural language description, from voice input, from a template or from agent skills. The backend is Python with FastAPI, the frontend is Vue and TypeScript, and the whole system is packaged for Docker so a single script or a released container image brings up a local instance. Once a workflow exists it can be invoked several ways: from the canvas itself, through REST execution endpoints, through server-sent-event streaming, from MCP clients, or through a public portal chat interface that exposes the workflow to end users. Observability is treated as a core feature rather than a paid tier: run history, LLM traces, evaluation runs, logs, OpenTelemetry export and real dollar cost tracking per execution are all included in the self-hostable product. The project argues explicitly against gating production features such as global variables, execution search, insights, audit logs, team controls and customer-facing portals behind enterprise licensing. Supported capabilities listed by the maintainers include multi-agent orchestration, retrieval-augmented generation pipelines, Model Context Protocol support both as a server and as a client, and human-in-the-loop review steps where a person approves or edits before execution continues. Licensing is MIT with a Commons Clause condition, which makes it source-available rather than fully open source. The intended users are teams that want to build and operate agentic business processes on their own infrastructure while keeping visibility into every model call and its cost.
https://github.com/heymrun/heym
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