# 🚀 Deployment Guide - Excel Analyser MCP
This guide will help you deploy Excel Analyser MCP to the cloud so others can use it via HTTP transport.
## 🛤️ Railway Deployment (Recommended)
### Step 1: Prepare Your Repository
1. **Clone/Fork the repository**
```bash
git clone https://github.com/contactakagrawal/excel-analyser-mcp.git
cd excel-analyser-mcp
```
2. **Verify files are in place**
- ✅ `Procfile` (tells Railway how to start the server)
- ✅ `package.json` (with updated dependencies)
- ✅ `excel-analyser-mcp.js` (with HTTP transport support)
### Step 2: Deploy to Railway
#### Option A: Via Railway Dashboard
1. Go to [Railway.app](https://railway.app)
2. Click "New Project" → "Deploy from GitHub repo"
3. Select your excel-analyser-mcp repository
4. Railway will automatically detect it's a Node.js project
5. Deployment starts automatically!
#### Option B: Via Railway CLI
```bash
# Install Railway CLI
npm install -g @railway/cli
# Login to Railway
railway login
# Deploy
railway up
```
### Step 3: Configure Environment (Optional)
In Railway dashboard → your project → Variables:
```
PORT=8080 # Railway sets this automatically
NODE_ENV=production # Optional: for production optimizations
```
### Step 4: Access Your Deployed Server
After deployment, Railway provides a URL like: `https://your-app.railway.app`
**Test endpoints:**
- **Health check**: `https://your-app.railway.app/health`
- **MCP endpoint**: `https://your-app.railway.app/mcp`
## 🔗 Using Your Deployed MCP Server
### For MCP Clients (Claude Desktop, Cursor, etc.)
Add to your MCP client configuration:
```json
{
"mcpServers": {
"Excel Analyser MCP (Cloud)": {
"type": "http",
"url": "https://your-app.railway.app/mcp"
}
}
}
```
### For Web Applications
```javascript
// Example: Connect from a web app
const mcpClient = new MCPClient({
name: "MyApp",
version: "1.0.0"
});
await mcpClient.connect({
type: "httpStream",
url: "https://your-app.railway.app/mcp"
});
// Use the tools
const result = await mcpClient.callTool({
name: "read_excel",
arguments: { filePath: "/path/to/file.xlsx" }
});
```
## 📁 File Access Considerations
**Important**: Your deployed server can only access files that are:
1. **Uploaded to the server** (need to implement file upload)
2. **Publicly accessible via URL** (modify tools to accept URLs)
3. **Included in the deployment** (static files)
### Solution Options:
#### Option 1: URL-based File Access
Modify tools to accept URLs:
```javascript
// Instead of local file path
{ filePath: "./data.xlsx" }
// Use public URLs
{ filePath: "https://example.com/data.xlsx" }
```
#### Option 2: Base64 File Upload
Accept base64-encoded file content:
```javascript
{
fileContent: "data:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet;base64,UEsDBBQA...",
fileName: "data.xlsx"
}
```
#### Option 3: Cloud Storage Integration
Integrate with AWS S3, Google Cloud Storage, etc.
## 🌐 Alternative Deployment Platforms
### Vercel
```bash
npm install -g vercel
vercel --prod
```
Add `vercel.json`:
```json
{
"version": 2,
"builds": [
{
"src": "excel-analyser-mcp.js",
"use": "@vercel/node"
}
],
"routes": [
{
"src": "/(.*)",
"dest": "/excel-analyser-mcp.js"
}
]
}
```
### Heroku
```bash
# Install Heroku CLI, then:
heroku create your-app-name
git push heroku main
```
### Google Cloud Run
```dockerfile
# Dockerfile
FROM node:18
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
EXPOSE 8080
CMD ["node", "excel-analyser-mcp.js", "streamableHttp"]
```
## 🔒 Security Considerations
### For Production Deployment:
1. **Rate Limiting**
```javascript
// Add rate limiting middleware
const rateLimit = require('express-rate-limit');
```
2. **Authentication** (if needed)
```javascript
// Add API key validation
if (req.headers['x-api-key'] !== process.env.API_KEY) {
return res.status(401).json({ error: 'Unauthorized' });
}
```
3. **CORS Configuration**
```javascript
// Restrict to specific origins in production
res.setHeader('Access-Control-Allow-Origin', 'https://yourdomain.com');
```
4. **File Size Limits**
```javascript
// Limit file upload sizes
const maxFileSize = 50 * 1024 * 1024; // 50MB
```
## 📊 Monitoring & Maintenance
### Health Checks
Your server includes a health check endpoint:
```
GET https://your-app.railway.app/health
```
### Logs
Check Railway dashboard → your project → Deployments → View logs
### Updates
Push to your GitHub repository → Railway auto-deploys
## 🆘 Troubleshooting
### Common Issues:
1. **Port Issues**
- Ensure you're using `process.env.PORT`
- Railway assigns port automatically
2. **File Access**
- Remember: deployed server can't access local files
- Use URLs or implement file upload
3. **CORS Errors**
- Check allowed origins in CORS headers
- Ensure proper headers for MCP
4. **Memory Limits**
- Large files may exceed Railway's memory limits
- Consider chunking or streaming for large files
### Getting Help:
- **Railway Discord**: https://discord.gg/railway
- **GitHub Issues**: https://github.com/contactakagrawal/excel-analyser-mcp/issues
- **Email**: contactakagrawal@gmail.com
---
## 🎉 Success!
Once deployed, share your MCP server URL with others:
**Your MCP Server**: `https://your-app.railway.app/mcp`
Users can connect to it from any MCP-compatible client! 🚀
