HEYM
About
Self-hosted AI workflow automation platform with visual canvas, agents, RAG, HITL, MCP, and observability in one runtime. Expose your Heym workflows as an MCP server at /api/mcp/sse — callable from Claude Desktop, Cursor, or any MCP client.
Explore
- Visual drag-and-drop workflow canvas with 30+ node types
- AI Assistant: describe workflows in natural language
- LLM & Agent nodes with tool calling and persistent memory
- Multi-agent orchestration (orchestrator + sub-agents)
- Human-in-the-Loop (HITL) checkpoints
- Built-in RAG with QDrant vector stores
- MCP client & server support
- Portal: publish workflows as public chat UIs
- LLM traces, cost tracking, and evals
- Self-hosted — your data, your infrastructure
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
HEYMCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
``bash`
git clone https://github.com/heymrun/heym.git
cd heym
cp .env.example .env
./run.sh
http://localhost:4017
Then open the editor at .
Add this to your MCP client configuration:
`json``
{
"mcpServers": {
"heym": {
"url": "http://localhost:4017/api/mcp/sse"
}
}
}
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"heym": {
"heym": {
"url": "http://localhost:4017/api/mcp/sse"
}
}
}
}
McpServers
{
"heym": {
"url": "http://localhost:4017/api/mcp/sse"
}
}
What is Heym?
Heym is a self-hosted, source-available AI workflow automation platform built around LLMs, agents, and intelligent tooling. Wire together AI agents, vector stores, web scrapers, HTTP calls, and message queues on a visual canvas — then deploy instantly via Docker.Sign in to leave a review
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