Run AI coding agents in hardened container sandboxes.

run a fleet of AI agents on your own Kubernetes

Markdown that runs — one file, any agent.

Self-hosted control plane for AI agents: dispatch tasks, review runs, track spend, and operate OpenClaw, Claude Code, Codex, and other runtimes.

Agent Skill evaluation harness for paired variants, trace artifacts, and runner adapters

Multi-language agent runtime and library for execution scope management, lifecycle events, and middleware on tool and LLM calls.

Open-source customer money path for usage-based SaaS — authorize customer spend before paid work runs.

55 framework-portable UI components for Astro, React, and Vue. Install accessible Tailwind CSS components as source you own, backed by a shared framework-neutral Runtime.

Install, run and deploy your own decentralized AI agent service

A server that helps people access and query data in databases using the Legion Query Runner with Model Context Protocol (MCP) in Python.

A test runner for agentskills.io-style AI agent skills

CTX - Context Runtime Engine for Coding Agents

Orchestrate AI coding agents (Claude Code, Codex) as parallel subagents over tmux — a loop-engineering runtime with auto-continue, execute-then-review, and cross-session memory.

TypeScript multi-agent framework that runs in your own environment: consequential actions wait for approval and every run leaves a verifiable record. Describe the goal, not the graph. 13 built-in providers (Claude, OpenAI, Gemini, DeepSeek and more) plus any OpenAI-compatible endpoint, local models included.

A Model Context Protocol (MCP) server that enables LLMs to run ANY code safely in isolated Docker containers.

Collective intelligence runtime for AI agents. Knowledge graph + persistent memory.

🦭 Run and operate MariaDB in a cloud native way

Open-Source Platform for Subagents and Agent Teams. Long-running, collaborative, proactive.

Deterministic safety solutions for probabilistic AI agents

Secure MCP runtime for AI agents to operate local machines, servers, and containers with multi-device orchestration.

A dashboard for running and coordinating multiple AI CLI agents at once.

The theory of LLM wikis, running as one. A framework for agent-operated knowledge: typed, linked, review-gated markdown your agents execute.

Universal memory runtime for AI agents

The multi-agent harness that checks the work: verifies agent runs by artifacts (stop-hook gates, independent judges, append-only event logs) across Claude Code, Codex, Cursor, and 10+ runtimes.