Deploy Any MCP Server with CloudMCP's Custom Deployment Feature

CloudMCP now lets you deploy any MCP (Model Context Protocol) server, not just those in our curated registry. Whether your server is published on NPM, PyPI, or hosted on GitHub, you can deploy it with just a few clicks using our new custom deployment feature.

Prerequisites

Before you begin, ensure you have:

• A cloudmcp.run account (sign up with GitHub at cloudmcp.run)
• The package name or GitHub URL of the MCP server you want to deploy
• Any required API keys or environment variables for your server
• (Coming Soon!) Authentication tokens for private packages

What's New?

The custom deployment feature enables:

• Universal package support: Deploy from NPM, PyPI, or GitHub repositories
• Private package deployment: Use authentication tokens for private resources
• Real-time validation: Instant package verification as you type
• Smart detection: Automatic recognition of package vs repository inputs
• Flexible configuration: Full control over arguments and environment variables

Step 1: Access Custom Deployment

Navigate to your CloudMCP dashboard and open the Deployments page. Scroll down to find the new "Custom Deployment" section.

Loading image...Custom Deployment section showing Deploy Custom Server button

Click the "Deploy Custom Server" button to open the deployment configuration dialog.

Step 2: Configure Your Package Manager

The custom deployment dialog opens with a clean interface for configuring your server.

Loading image...Custom Deployment dialog showing package manager selection and input fields

Select Your Package Manager

Choose from four popular package managers based on your server's language:

• NPX - For Node.js packages (most MCP servers)
• UVX - For Python packages using UV
• PIPX - For traditional Python packages
• BUNX - For Bun runtime packages

The package manager determines how CloudMCP will install and run your server.

Step 3: Enter Your Package or Repository

Smart Input Detection

CloudMCP automatically detects what type of resource you're entering:

Loading image...Package input field showing smart detection with package icon

• Package name: Shows a package icon (📦)

  • NPM: @modelcontextprotocol/server-filesystem
  • PyPI: mcp-server-sqlite

• GitHub repository: Shows a GitHub icon (🐙)

  • https://github.com/owner/repo
  • github.com/owner/repo

Real-time Validation

As you type, CloudMCP validates your input in real-time:

Loading image...Real-time validation showing successful package verification

The validation checks:

• Package exists in the selected registry
• Latest version available
• Whether authentication is required
• Package metadata and description

💡 Tip: The validation happens automatically after you stop typing for 500ms, preventing unnecessary API calls while you type.

Step 5: Add Configuration

Deployment Name

Give your deployment a descriptive name to identify it in your dashboard.

Good naming examples:

• production-database-server
• dev-filesystem-access
• customer-api-integration

Command Arguments (Optional)

Add any additional command-line arguments your server needs:

Loading image...Arguments field showing example arguments

Common use cases:

• Specify configuration files: --config /path/to/config.json
• Set operation modes: --mode production
• Enable features: --enable-feature-x

Environment Variables

Configure environment variables through the intuitive interface:

Loading image...Environment variables interface with add/remove buttons

To add variables:

1. Click "Add Variable"
2. Enter the key (e.g., API_KEY)
3. Enter the value
4. Add more as needed
5. Remove unwanted variables with the trash icon

🔒 Security Tip: CloudMCP blocks potentially dangerous environment variables like LD_PRELOAD and NODE_OPTIONS for security.

Step 6: Deploy Your Server

Once everything is configured, click "Deploy Server" to launch your deployment.

CloudMCP will:

1. Create a dedicated instance for your server
2. Install the package from your selected registry
3. Apply all environment variables securely
4. Start the server with your specified arguments
5. Provide you with a unique endpoint URL

Step 7: Monitor Your Deployment

After deployment, you'll see your custom server in the Active Deployments section:

Loading image...Active deployment card showing custom badge and server details

Custom Deployment Indicators

Custom deployments are easy to identify:

• "Custom" badge: Distinguishes from registry servers
• Package info: Shows the exact package or repository deployed
• Status indicator: Real-time deployment status
• Server URL: Your unique endpoint for connecting

Available Actions

• Copy URL: Get your server endpoint
• Install in VSCode: One-click VSCode integration
• Stop: Shut down when no longer needed

Use Cases

Deploy Your Own MCP Server

Testing a server you're developing:

Package: github.com/yourname/my-mcp-server
Branch: feature-branch (optional)

Use Community Servers

Deploy servers not yet in our registry:

Package: @community/awesome-mcp-server
Version: latest

Private Organization Servers

Deploy internal company servers:

Package: @mycompany/internal-mcp-server
Token: npm_token_xxxxx
Environment: COMPANY_API_KEY=xxxxx

Experimental Features

Test bleeding-edge versions:

Package: mcp-server-experimental@beta
Arguments: --experimental-mode

Trial vs Paid Deployments

CloudMCP offers flexible deployment options:

Trial Deployments

• Duration: 48 hours
• Perfect for: Testing and development
• Limit: Based on your account type
• Automatic expiry: Servers stop after 48 hours

Paid Deployments

• Duration: Unlimited
• Perfect for: Production use
• Resources: Dedicated instances
• Support: Priority support included

Security Features

The custom deployment feature includes enterprise-grade security:

Rate Limiting

• Validation: 20 requests per minute
• Deployment: 10 deployments per minute
• Per-user limits: Prevents abuse

Input Protection

• SQL injection prevention: Escaped LIKE patterns
• Command injection blocking: Sanitized inputs
• Path traversal protection: Validated file paths

Request Management

• Deduplication: Prevents duplicate deployments
• Atomic operations: Database-level constraints
• Transaction safety: Rollback on errors

Environment Security

• Blocked variables: Dangerous vars like LD_PRELOAD blocked
• Token encryption: Secure storage of authentication tokens
• Secret masking: Never exposed in logs or UI

Best Practices

1. Validate Before Deploying

Let the real-time validation complete before clicking deploy. This catches issues early and saves time.

2. Use Descriptive Names

Help your future self by using clear, descriptive deployment names:

• ❌ server1
• ✅ production-github-integration

3. Secure Your Tokens

• Never share authentication tokens
• Rotate tokens regularly
• Use minimal required permissions

4. Test with Trials First

Use trial deployments to:

• Test server functionality
• Verify environment variables
• Check performance requirements

5. Clean Up Unused Deployments

Regular maintenance keeps your dashboard organized:

• Delete stopped deployments
• Remove expired trials
• Archive old configurations

Troubleshooting

Validation Fails

Package not found error:

• Verify the package name spelling
• Check the package exists in the selected registry
• For GitHub, ensure the URL format is correct

Version not available:

• Check if the version exists
• Try using latest or no version
• For GitHub, verify the branch name

Deployment Failures

Environment variable errors:

• Check for typos in variable names
• Verify required variables are set
• Ensure values don't contain invalid characters

Resource limits:

• Check your deployment quota
• Upgrade plan if needed
• Delete unused deployments

Connection Problems

Can't connect to deployed server:

• Verify the server started successfully
• Check server logs for errors
• Ensure your client supports the server's MCP version

Advanced Tips

Using GitHub Branches

Deploy specific branches or commits:

github.com/owner/repo#branch-name
github.com/owner/repo#commit-hash

Package Versions

Specify exact versions for stability:

NPM: @package/name@1.2.3
PyPI: package-name==1.2.3

Multiple Configurations

Deploy the same server multiple times:

• Different environment variables for dev/prod
• Separate instances for different projects
• Isolated deployments for testing

Monitoring Deployments

Track your custom deployments:

• Check status indicators regularly
• Monitor resource usage (coming soon)
• Set up alerts for failures (coming soon)

What's Next?

Now that you've mastered custom deployments:

• 🚀 Deploy your servers: Start with your own MCP servers
• 📦 Try different registries: Explore NPM, PyPI, and GitHub options
• 🔒 Deploy private packages: Use authentication for internal servers
• 💡 Share your servers: Contribute to the MCP ecosystem

Coming Soon

We're constantly improving custom deployments:

• Deployment templates: Save configurations for reuse
• Bulk deployments: Deploy multiple servers at once
• Version management: Easy updates and rollbacks
• Performance metrics: Detailed resource monitoring

Need Help?

If you encounter any issues:

• Check our blog for updates and tutorials
• Join our Discord community
• Email support at vikash@cloudmcp.run

Ready to deploy your custom MCP server? Start deploying →