An orchestration runtime for multi-agent AI systems. Declare agents, tools, and policies as YAML; Orloj schedules, executes, routes, and governs them for production-grade operation.
Ship fast. Ship right. Ship everything. Ship accountably. AI-powered dev system: slash commands orchestrate specialist agents from idea to hardened production. Imports godplans plans and godaudits reports; artifacts as .mdx.
Write once. Generate everything. A modular, open-source ecosystem for building durable, observable, multimodal AI systems. Text, voice, image, video, music — one unified interface, any provider, any model, local or cloud.
The agent framework where the model never holds the trigger — every consequential action clears your policy first, waits for a human when it matters, and lands on a record you can verify. Build on it, or put it around the agent you already have.
subagent-mcp is an MCP stdio server that turns an AI coding assistant (Claude Code, Codex, Gemini CLI) into a manager of local Claude and Codex sub-agents on macOS, Linux, and Windows.
Self-hosted runtime for AI agents and workflows. Durable execution, capability-gated tools, human approval gates, and a memory system that accumulates. Runs survive restarts and resume where they stopped. Mount your domain logic as a plugin package or drive it over the HTTP SDK
Workflow engine where ops can yield — same async DAG handles batch jobs and event-driven streaming pipelines (pipecat-style callbot, STT → LLM → TTS). Python frontend, drop-in Rust runtime; 2–3× faster on chains, 10–30× on production workloads. LLMs, agents, RAG, native compute as first-class ops.
Mandrel is an orchestration and harness for agentic AI coding. It ships a system prompt, personas, a two-tier skill library, baseline rules, slash-command workflows, and a GitHub-backed orchestration engine — distributed as a Git submodule into your project's .agents/ directory.
Multi-agent AI orchestration platform for automation, workflows, and developer tools. Golutra transforms Codex, Claude Code, and OpenClaw into a unified agent system with parallel execution, task orchestration, long-running workflows, and AI productivity workspace.
Multi-agent code review mesh — orchestrates AI agents from multiple providers to review code in parallel, cross-review each other's findings, and build accuracy profiles over time. Agents that catch real bugs get picked more often. Agents that hallucinate get deprioritized. MCP server for Claude Code, Cursor, and other IDEs.
CLI-first orchestration for AI coding agents: run selected agents and models in parallel, compare raw answers, and coordinate review or implementation workflows.