How does Station integrate with Claude Code?

Station provides specialized MCP tools (available via 'stn stdio') that allow Claude to programmatically execute agents, query environments, and manage run histories directly within the conversation.

Does Station offer observability for AI agent actions?

Yes, Station has built-in support for Jaeger, allowing you to view detailed traces of every agent step, tool call, and model interaction.

Can I use Station for multi-agent orchestration?

Yes, Station supports a coordinator pattern using '.prompt' files, allowing a primary agent to delegate tasks to specialized sub-agents and synthesize their results.

What is the primary purpose of Station?

Station is an open-source runtime and CLI for deploying, running, and managing AI agents on your own infrastructure rather than relying on third-party black-box platforms.

Which cloud providers are supported for deployment?

Station currently supports deployment to Fly.io, any Kubernetes cluster, and traditional servers via Ansible, providing flexible hosting options.

Station Agent Runtime

Name: Station Agent Runtime
Author: cloudshipai

bycloudshipai

•

377

部署与 DevOps

Orchestrates and deploys AI agents with full infrastructure control using a self-hosted runtime and CLI toolset.

关于

Station is an open-source orchestration platform designed for teams that need to deploy and manage AI agents on their own infrastructure. It provides a robust CLI (`stn`) and over 41 MCP tools to handle agent creation, environment synchronization, and multi-agent coordination. With built-in support for observability via Jaeger and flexible deployment options for Fly.io, Kubernetes, and Ansible, Station bridges the gap between local agent development and production-grade agentic workflows, offering developers complete control over their agentic stack.

主要功能

Support for multi-agent hierarchies and coordinator patterns
Automated environment synchronization and secure secret management
CLI and MCP toolset for end-to-end agent management and execution
Multi-target deployment to Fly.io, Kubernetes, and Ansible-managed servers
377 GitHub stars
Native observability integration with Jaeger for detailed execution tracing

使用场景

Creating self-hosted agent teams with strict infrastructure requirements and data privacy controls
Managing complex agentic workflows that require human-in-the-loop approvals and multiple MCP servers
Deploying a fleet of specialized AI agents for production incident response and system monitoring

关于

主要功能

Support for multi-agent hierarchies and coordinator patterns
Automated environment synchronization and secure secret management
CLI and MCP toolset for end-to-end agent management and execution
Multi-target deployment to Fly.io, Kubernetes, and Ansible-managed servers
377 GitHub stars
Native observability integration with Jaeger for detailed execution tracing

使用场景

Creating self-hosted agent teams with strict infrastructure requirements and data privacy controls
Managing complex agentic workflows that require human-in-the-loop approvals and multiple MCP servers
Deploying a fleet of specialized AI agents for production incident response and system monitoring