The definitive platform for deploying Model Context Protocol (MCP) servers in production.

Zero-configuration deployment of production-ready MCP servers with Docker containers, comprehensive CLI tools, intelligent caching, and enterprise-grade management features. Focus on AI integration, not infrastructure setup.

⚠️ This version is in maintenance mode. Please migrate to MCP Platform for latest features and updates.

Deploy Model Context Protocol (MCP) servers in seconds, not hours.

Zero-configuration deployment of production-ready MCP servers with Docker containers, comprehensive CLI tools, and intelligent caching. Focus on AI integration, not infrastructure setup.

# Install MCP Templates
pip install mcp-platform

# List available templates
mcpp list

# Deploy instantly
mcpp deploy demo

# View deployment
mcpp logs demo

That's it! Your MCP server is running at http://localhost:8080

Perfect for: AI developers, data scientists, DevOps teams building with MCP.

Deploy MCP servers instantly with pre-built templates—no Docker knowledge required.

Automatically finds and showcases every tool your server offers.

6-hour template caching with automatic invalidation for lightning-fast operations.

Comprehensive command-line interface for deployment, management, and tool execution.

Configure via JSON, YAML, environment variables, CLI options, or override parameters.

Ready-to-use templates for common use cases: filesystem, databases, APIs, and more.

pip install mcp-platform

docker run --privileged -it dataeverything/mcp-server-templates:latest deploy demo

git clone https://github.com/DataEverything/mcp-server-templates.git
cd mcp-server-templates
pip install -r requirements.txt

# Basic deployment
mcpp deploy filesystem --config allowed_dirs="/path/to/data"

# Advanced overrides
mcpp deploy demo --override metadata__version=2.0 --transport http

# List all deployments
mcpp list --deployed

# Stop a deployment
mcpp stop demo

# View logs
mcpp logs demo --follow

# Create new template
mcpp create my-template

# Test locally
mcpp deploy my-template --backend mock

┌─────────────┐    ┌───────────────────┐    ┌─────────────────────┐
│  CLI Tool   │───▶│ DeploymentManager │───▶│ Backend (Docker)    │
│  (mcpp)     │    │                   │    │                     │
└─────────────┘    └───────────────────┘    └─────────────────────┘
       │                      │                        │
       ▼                      ▼                        ▼
┌─────────────┐    ┌───────────────────┐    ┌─────────────────────┐
│ Template    │    │ CacheManager      │    │ Container Instance  │
│ Discovery   │    │ (6hr TTL)         │    │                     │
└─────────────┘    └───────────────────┘    └─────────────────────┘

Configuration Flow: Template Defaults → Config File → CLI Options → Environment Variables

View all templates →

mcpp deploy filesystem --config allowed_dirs="/home/user/data"

mcpp deploy gitlab \
  --config gitlab_token="$GITLAB_TOKEN" \
  --config read_only_mode=true \
  --override metadata__version=1.2.0 \
  --transport stdio

{
  "allowed_dirs": "/home/user/projects",
  "log_level": "DEBUG",
  "security": {
    "read_only": false,
    "max_file_size": "100MB"
  }
}

mcpp deploy filesystem --config-file myconfig.json

1. Use the generator:

   mcpp create my-template

2. Define template.json:

   {
     "name": "My Template",
     "description": "Custom MCP server",
     "docker_image": "my-org/my-mcp-server",
     "transport": {
       "default": "stdio",
       "supported": ["stdio", "http"]
     },
     "config_schema": {
       "type": "object",
       "properties": {
         "api_key": {
           "type": "string",
           "env_mapping": "API_KEY",
           "sensitive": true
         }
       }
     }
   }

3. Test and deploy:

   mcpp deploy my-template --backend mock

Full template development guide →

This repository has evolved into MCP Platform with enhanced features and better architecture.

1. Better Naming: "MCP Platform" better reflects the comprehensive nature of the project
2. Enhanced Architecture: Improved codebase structure and performance
3. Expanded Features: More deployment options, better tooling, enhanced templates
4. Future Growth: Better positioned for upcoming MCP ecosystem developments

• ✅ All your existing configurations work unchanged
• ✅ Same Docker images and templates
• ✅ Same deployment workflows
• ✅ Full backward compatibility during transition

1. Install new package:

   pip uninstall mcp-templates
   pip install mcp-platform

2. Update commands:

   # Old command
   mcpp deploy demo
   
   # New command (everything else identical)
   mcpp deploy demo

3. Update documentation bookmarks:

   • New docs: https://data-everything.github.io/MCP-Platform/
   • New repository: https://github.com/Data-Everything/MCP-Platform

• Current (Legacy) Package: Security updates only through 2025
• New Platform: Active development, new features, full support
• Migration Support: Available through Discord and GitHub issues

🚀 Start your migration now →

• Getting Started - Installation and first deployment
• CLI Reference - Complete command documentation
• Template Guide - Creating and configuring templates
• User Guide - Advanced usage and best practices

• Discord Server - Get help and discuss features
• GitHub Issues - Report bugs and request features
• Discussions - Share templates and use cases

This project is licensed under the Elastic License 2.0.

Built with ❤️ for the MCP community. Thanks to all contributors and template creators!