Post-Generation Orchestration
The automation layer that runs after an app is generated, turning a static app into a living system. In GenMB this means a visual workflow builder (20+ DAG-validated node types), scheduled Python agents on cron, chat agents on Telegram, Slack, and Email, MCP server support, and one-click deploy. It is what distinguishes GenMB from AI builders that stop at code generation.
Related Terms
Workflow
A visual automation pipeline in GenMB that connects triggers to actions using a node-based editor. Workflows support 16+ node types including AI processing, HTTP requests, conditional logic, loops, email, Slack, database queries, and code execution. Workflows can be triggered manually, on a schedule (cron), or via webhook. Validated as a DAG (directed acyclic graph) to prevent circular dependencies. Available on Business plan.
Backend Agent
A scheduled server-side AI agent in GenMB that runs Python scripts on a cron schedule via a shared GKE worker pool. Backend Agents can call APIs, process data, send emails, and trigger actions automatically. GenMB generates the agent code from a natural language description, deploys it, and manages execution logs. Available on Business plan, max 3 per user.
Chat Agent
An AI assistant connected to a messaging channel - Telegram, Slack, or Email - that answers questions and triggers actions against your app's data and tools. GenMB generates the agent from a natural language description and wires it to the channel, so users interact with your app conversationally without opening it.
MCP (Model Context Protocol)
An open standard by Anthropic for connecting AI tools to external services via a standardized protocol. GenMB exposes an MCP server with 7 tools (list apps, get app details, generate code, refine code, deploy, get deployment status, list templates) accessible to Claude Code, Cursor, and other MCP-compatible clients. Authenticate with a GenMB API key (genmb_sk_ prefix) via Streamable HTTP.
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