workflow-orchestration
11 servers · 1,084★ total
An open-source, PyTorch-like runtime for dynamic multi-agent and multi-session workflows.
Deploy production-ready AI services in minutes. One YAML file for agents, RAG pipelines, and MCP servers — run anywhere. Inspired by docker-compose.
⚡ Control Apache Airflow with natural language via MCP. Chat with your workflows using Claude, GPT, or any LLM — no REST API calls needed. Supports Airflow 2.x (43 tools) & 3.0+ (45+ tools).
Self-hosted control plane for AI coding agents (Claude Code, Codex, Gemini, Ollama). Shared MCPs, reusable workflows, AI audit that makes any repo AI-friendly. Engineering, not prompting : smaller prompts, fewer hallucinations, lower token bill.
🚀 Ultimate Developer Productivity Suite - 11 specialized MCP servers for AI-powered code analysis, security scanning, browser automation, and workflow orchestration. FastAPI + React + TypeScript + Docker ready.
Declarative multi-agent AI workflows in HCL. Single Go binary. Native MCP. Plugins in Go and Python.
LiAgent OS is a local-first AI agent OS for building a private personal assistant with governed autonomy across local models and hybrid cloud services. It brings conversation, tool use, multi-agent orchestration, task scheduling, heartbeat execution, human approval, and auditability into one long-lived loop.
A typed orchestration language for AI-generated, validated tool programs that execute locally—without model round-trips between steps.
AI-era Makefile, codify expert workflows as YAML graphs
Turn SpringDoc OpenAPI into production-ready MCP tools for Spring Boot: discovery, validation, workflows, and guardrails.
APAI is an open protocol for describing, documenting, and validating artificial intelligence systems.