homerail
Voice-first local agent orchestration runtime for auditable DAG workflows.
HomeRail is a TypeScript-based local agent orchestration runtime that transforms single-shot AI conversations into auditable, reusable directed acyclic graph (DAG) workflows. Designed to run on home servers, NAS devices, or homelabs, it coordinates multiple AI agents across explicit workflow nodes with voice input, generated UI output, and complete execution tracing. The platform isolates each agent's work in separate containers, enables replay and evaluation of runs, and supports multi-model configurations where expensive models handle planning while efficient models execute bulk tasks.
Key Features
Use Cases
- 01Running multi-stage software development workflows with separate planning, implementation, testing, review, and summarization agents
- 02Orchestrating home automation tasks through voice commands with auditable execution traces
- 03Building reusable approval and review workflows with quorum-based decision gates
- 04Developing and debugging complex agent workflows using coding agents to drive the CLI
- 05Cost-optimizing AI workloads by routing planning to expensive models and execution to cheaper ones
- 06Creating persistent, resumable workflows with multi-round execution and recovery boundaries
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homerail — FAQ
What is HomeRail?+
HomeRail is a local TypeScript runtime that orchestrates multiple AI agents in auditable DAG workflows, running on your own hardware with voice input and generated UI output. It replaces single-chat agent interactions with traceable, replayable workflows where each agent operates in its own isolated context.
How do I install HomeRail?+
Install Node.js 20+, npm 10+, and Docker, then clone the repository and run 'npm run install:all' and 'npm run build'. Link the CLI with 'cd homerail_cli && npm link', configure a model provider with 'hr model configure', and start the services with 'hr start'.
What AI models does HomeRail work with?+
HomeRail supports Claude Agent SDK-compatible models and includes harnesses for Codex, claude-sdk, kimi-code, and an experimental DeepSeek backend. You can configure different models per agent role, mixing expensive models for planning with cheaper ones for execution tasks.
Do I need API keys to use HomeRail?+
Yes, you need API credentials for at least one supported model provider. Configure credentials securely using 'hr model configure' with the '--api-key-stdin' flag, which stores them in the Manager's encrypted settings store rather than in repository files.
Is HomeRail free?+
HomeRail itself is MIT-licensed open source software, but you'll incur costs from the AI model providers you configure. Model usage costs depend on your chosen providers and the complexity of your DAG workflows.
Which platforms does HomeRail support?+
HomeRail runs on macOS (with Docker Desktop), Windows (Docker Desktop with WSL 2 or Hyper-V, using Git Bash or POSIX shell), and Linux (Docker Engine). It's designed for home servers, NAS devices, and homelabs with adequate disk space for workflow artifacts.
How do I install homerail?+
Open the source repository on GitHub and follow its README. homerail is a agent — MCP Agents Market links you directly to the official repo.
Is homerail free?+
homerail is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.