Flowcraft is a workflow orchestration framework for building, executing, and monitoring durable workflows. It provides a type-safe, composable API for defining workflows as directed graphs of nodes and edges, supporting both programmatic (fluent) and declarative (JSON) definitions. The framework enables progressive scaling from in-memory execution to distributed systems via adapters for message queues and cloud services, with built-in support for patterns like retries, timeouts, human-in-the-loop, batch processing, and subflows. Key architectural pieces include a dependency-free core runtime, a sophisticated context tracking system for efficient state persistence, a plugin-based adapter architecture for distributed execution, and LLM tooling for workflow introspection and control via natural language.
This repository is a monorepo of self-contained demo applications showing how to build and deploy multi-agent AI systems using Docker Compose, Docker Model Runner, and the MCP Gateway. It contains 12+ independent examples spanning Google ADK, A2A, Agno, CrewAI, LangGraph, Langchaingo (Go), Spring AI, Akka, and a Next.js agent UI. Each subproject is a standalone composition with its own compose.yaml, Dockerfile, and README, designed to run with a single `docker compose up --build` after creating a `.mcp.env` file. The demos are reference architectures rather than a single product, emphasizing local LLM inference, MCP tool integration, and switching between local and cloud models via compose override files.