Aporix MCP Server

MCP server that exposes the Aporix document optimization API as a tool for AI agents (ClawUp, OpenClaw, Claude Desktop, etc.).

Supports stdio (local agents) and HTTP/SSE (hosted endpoint) transport.

Tool: optimize_document

Inputs:

Outputs:

Related MCP server: mcp-schema-bloat-fixer

Local stdio (for local agents)

npm install
npm run build
npm start

Register in ~/.openclaw/openclaw.json:

{
  "mcpServers": {
    "aporix": {
      "command": "node",
      "args": ["/absolute/path/to/aporix-mcp-server/dist/index.js"]
    }
  }
}

Hosted HTTP/SSE (for ClawUp MCP submission)

Run locally

npm run dev:http
# Server starts on http://localhost:3001/mcp

Endpoints

Deploy to Railway

# Install Railway CLI
npm i -g @railway/cli

# Login and deploy
railway login
railway init
railway up

# Set environment variable
railway env set APORIX_API_URL=https://your-domain.vercel.app/api/optimize

Railway auto-detects the Dockerfile and sets PORT.

Deploy to Render

1. Create a new Web Service

2. Connect your GitHub repo

3. Use these settings:

   • Runtime: Docker

   • Health Check Path: /health

4. Add environment variable:

   • APORIX_API_URL: https://your-domain.vercel.app/api/optimize

Deploy to Fly.io

fly launch
fly secrets set APORIX_API_URL=https://your-domain.vercel.app/api/optimize
fly deploy

Submit to ClawUp

Once deployed, paste your public MCP endpoint URL:

https://your-app.railway.app/mcp

into ClawUp's MCP Tool Submission form. The endpoint follows the Model Context Protocol over SSE transport.

Environment Variables

Testing

# Stdio test
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | node dist/index.js

# HTTP test (after starting with npm run dev:http)
curl http://localhost:3001/health