How do I deploy arifOS MCP Server on Railway?

You can deploy arifOS MCP Server on Railway by clicking the "Deploy Now" button on this page. Railway will automatically set up all the necessary services and configurations for you.

What are the system requirements?

Railway handles all the infrastructure requirements. You only need a web browser to deploy and manage your application.

Is this template free to use?

Yes, this template is free to use within your existing Railway account.

Can I customize this template?

Yes, you can fully customize this template. After deployment, you will have full control of what you've deployed in your Railway project.

How do I get support for this template?

You can get support through our community forum: arif-os-mcp-server-bbcb2a7b, or click "Get template help" for this template for more assistance.

Deploy and Host arifOS MCP Server on Railway

arifOS is an open-source Constitutional AI governance framework implementing the Model Context Protocol (MCP). It provides 6 specialized tools (INIT_000, AGI_GENIUS, ASI_ACT, APEX_JUDGE, VAULT_999, Trinity Loop) enforcing 13 thermodynamic floors for safe AI orchestration with Streamable HTTP and SSE transport.

About Hosting arifOS MCP Server

Deploying arifOS MCP Server gives you a production-ready Constitutional AI governance endpoint. The server runs as a FastAPI/Uvicorn ASGI application, exposing MCP tools via Streamable HTTP at /mcp and legacy SSE fallback. It includes health monitoring at /health, JSON metrics at /metrics/json, and automatic enforcement of 13 constitutional floors (Amanah, Truth, Humility, etc.) across all AI operations. The Docker-based deployment uses Python 3.11-slim with uv package manager for fast, reproducible builds.

Common Use Cases

AI Agent Orchestration: Govern multi-agent systems with constitutional guardrails and thermodynamic enforcement across Claude, GPT, Gemini integrations
MCP Protocol Bridge: Expose arifOS governance tools to any MCP-compatible client (Claude Desktop, Cline, Zed) via Streamable HTTP transport
Research & Development: Test Constitutional AI frameworks, AGI safety protocols, and thermodynamic governance in production environments

Dependencies for arifOS MCP Server Hosting

Python 3.11+ with FastAPI, Uvicorn, MCP SDK, httpx-sse, and sse-starlette
Docker (Railway uses your Dockerfile with uv package manager for dependency isolation)
GitHub Repository: Source code at github.com/ariffazil/arifOS (main branch)

Deployment Dependencies

Model Context Protocol Specification - Official MCP standard
FastMCP Python SDK - MCP server framework
arifOS Documentation - Governance floors and architecture

Implementation Details

The template uses a console script entry point defined in pyproject.toml:

[project.scripts]
codebase-mcp-sse = "codebase.mcp:main"

Health endpoint returns governance status:

{
  "status": "ok",
  "version": "v53.2.0-CODEBASE",
  "tools": 6,
  "mode": "bridge",
  "cluster": 3
}

All 8 environment variables are pre-configured for production deployment with thermodynamic cluster level 3.

Why Deploy arifOS MCP Server on Railway?

Railway is a singular platform to deploy your infrastructure stack. Railway will host your infrastructure so you don't have to deal with configuration, while allowing you to vertically and horizontally scale it.

By deploying arifOS MCP Server on Railway, you are one step closer to supporting a complete full-stack application with minimal burden. Host your servers, databases, AI agents, and more on Railway.