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MCP Server Templates

Production-ready deployment system for Model Context Protocol (MCP) servers with zero-configuration deployment, comprehensive tool discovery, and enterprise-grade management capabilities.

MCP Server Templates is a self-hosted deployment system that enables rapid deployment, management, and scaling of MCP servers on your own infrastructure. It provides a unified CLI, flexible configuration system, advanced tool discovery, and pre-built templates for common use cases.

� What’s Inside

Welcome to the MCP Platform—where server deployment meets pure excitement! Here’s what makes this project a must-have for every AI builder:

⚡ Features (Mid-August 2025 Release)

🚀 Current Features

  • 🖱️ One-Click Docker Deployment: Launch MCP servers instantly with pre-built templates—no hassle, just pure speed.
  • 🔎 Smart Tool Discovery: Automatically finds and showcases every tool your server can offer. No more guesswork!
  • 💻 Slick CLI Management: Command-line magic for easy, powerful control over all deployments.
  • 🤝 Bring Your Own MCP Server: Plug in your own MCP server and run it on our network—even with limited features!
  • 🐳 Effortless Docker Image Integration: Add any existing MCP Docker image to the templates library with minimal setup and unlock all the platform’s cool benefits.
  • ⚡ Boilerplate Template Generator: Instantly create new MCP server projects with a CLI-powered generator—kickstart your next big idea!
  • 🛠️ Multiple Ways to Set Configuration: Flex your setup with config via JSON, YAML, environment variables, CLI config, or CLI override options—total flexibility for every workflow!

🌈 Planned Features

  • 🦸 MCP Sidekick (Coming Soon): Your friendly AI companion, making every MCP server compatible with any AI tool or framework.
  • 🛸 Kubernetes Support: Deploy to Kubernetes clusters with ease, scaling your MCP servers effortlessly.

Release Timeline: All this and more dropping mid-August 2025—don’t miss out!

Ready to dive in? Get Started with the README!

�🌟 MCP Platform - Managed Cloud Solution

Looking for enterprise deployment without infrastructure management? MCP Platform offers:

  • One-click deployment - Deploy any MCP server template instantly
  • 🛡️ Enterprise security - SOC2, GDPR compliance with advanced security controls
  • 📊 Real-time monitoring - Performance metrics, usage analytics, and health dashboards
  • 🔧 Custom development - We build proprietary MCP servers for your specific needs
  • 💼 Commercial support - 24/7 enterprise support with SLA guarantees
  • 🎯 Auto-scaling - Dynamic resource allocation based on demand
  • 🔐 Team management - Multi-user access controls and audit logging

Ready for production? Get started with MCP Platform →


Open Source Self-Hosted Deployment

This repository provides comprehensive tools for self-managing MCP server deployments on your own infrastructure.

🚀 Key Features

  • 🎯 Zero Configuration Deployment - Deploy templates with a single command
  • 🔍 Advanced Tool Discovery - Automatic detection of MCP server capabilities using official MCP protocol
  • 📦 Pre-built Templates - Production-ready templates for file operations, databases, APIs, and more
  • 🔧 Flexible Configuration - Multi-source configuration with environment variables, CLI options, and files
  • 🐳 Docker-First Architecture - Container-based deployments with proper lifecycle management
  • 📋 Rich CLI Interface - Beautiful command-line interface with comprehensive help and examples
  • 🧪 Template Development Tools - Complete toolkit for creating and testing custom templates
  • 📊 Monitoring & Management - Real-time status monitoring, log streaming, and health checks
  • 🔗 Integration Examples - Ready-to-use code for Claude Desktop, VS Code, Python, and more

🎯 Quick Start

Installation

# Install from PyPI (recommended)
pip install mcp-templates

# Verify installation
mcp-template --version

Deploy Your First Template

# List available templates
mcp-template list

# Deploy demo server
mcp-template deploy demo

# Discover available tools
mcp-template tools demo

# Get integration examples
mcp-template connect demo --llm claude

Integration with Claude Desktop

# Get container name
mcp-template list

# Update Claude Desktop config
mcp-template connect demo --llm claude

Claude Desktop Configuration:

{
  "mcpServers": {
    "demo": {
      "command": "docker",
      "args": ["exec", "-i", "CONTAINER_NAME", "python", "-m", "src.server"]
    }
  }
}

📚 Documentation

🚀 Getting Started

📖 User Guide

🛠️ CLI Reference

  • Command Overview - Complete CLI documentation
  • deploy - Deploy HTTP transport templates with configuration options
  • run-tool - Execute tools from stdio MCP servers
  • tools - Discover and analyze MCP server capabilities
  • tools - List tools from templates OR discover from Docker images
  • ~~discover-tools~~ - DEPRECATED: Use tools --image instead
  • connect - Generate integration examples for LLMs
  • config - View template configuration options
  • list - List templates and deployments
  • logs - Monitor deployment logs
  • status - Check deployment health

🔧 Development

🏗️ System Architecture

🎯 Use Cases

File Operations

# Deploy secure file server
mcp-template deploy file-server \
  --config security__allowed_dirs='["/data", "/workspace"]' \
  --config security__read_only=false

# Connect to Claude Desktop for file operations
mcp-template connect file-server --llm claude

Database Integration

# Deploy PostgreSQL MCP server
mcp-template deploy postgres-server \
  --config database__host=localhost \
  --config database__name=mydb \
  --env POSTGRES_PASSWORD=secret

# Generate Python integration code
mcp-template connect postgres-server --llm python

API Integration

# Deploy REST API integration server
mcp-template deploy api-server \
  --config api__base_url=https://api.example.com \
  --config api__auth_token=$API_TOKEN

# Test with cURL
mcp-template connect api-server --llm curl

🔍 Tool Discovery

Automatic MCP Protocol Discovery:

# Discover tools from any MCP-compliant Docker image
mcp-template tools --image mcp/filesystem /tmp

# Rich formatted output shows all capabilities:
 Discovered 11 tools via docker_mcp_stdio
- read_file: Read complete file contents
- write_file: Create or overwrite files
- list_directory: List directory contents
- create_directory: Create directories
- ... and 7 more tools

Integration Ready:

# Get ready-to-use integration code
mcp-template tools demo --format json
mcp-template connect demo --llm vscode

📊 Available Templates

Template Description Use Cases
demo Basic greeting and echo server Learning, testing, examples
file-server Secure filesystem operations Document processing, file management
postgres-server PostgreSQL database integration Data analysis, query execution
api-server REST API client with auth External service integration
mongodb-server MongoDB document operations NoSQL data operations
redis-server Redis cache and pub/sub Caching, real-time messaging

🛠️ System Requirements

  • Operating System: Linux, macOS, Windows (with WSL2)
  • Docker: Version 20.10+ (required for container deployments)
  • Python: Version 3.9+ (for CLI and development)
  • Memory: 512MB minimum, 2GB recommended
  • Storage: 1GB minimum for templates and container images

🚦 Production Deployment

Security Considerations

# Deploy with security hardening
mcp-template deploy file-server \
  --config security__read_only=true \
  --config security__max_file_size=10 \
  --config logging__enable_audit=true \
  --env MCP_ALLOWED_DIRS='["/secure/data"]'

Monitoring Setup

# Health check monitoring
mcp-template list --format json | jq '.summary'

# Log monitoring
mcp-template logs file-server --follow --since 1h

Backup and Recovery

# Export deployment configuration
mcp-template status file-server --format json > backup.json

# Cleanup and redeploy
mcp-template cleanup file-server
mcp-template deploy file-server --config-file backup.json

🤝 Community & Support

🗺️ Roadmap

  • Kubernetes Backend: Native Kubernetes deployment support
  • Template Marketplace: Community-driven template sharing
  • GraphQL Integration: GraphQL API server templates
  • Metrics & Alerting: Prometheus/Grafana integration
  • Multi-tenant Support: Isolated deployments for teams
  • Auto-scaling: Dynamic resource allocation

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.


Get started today: Choose between our managed cloud platform for instant deployment or self-hosted deployment for full control.

Install dependencies

pip install -e .

#### Basic Usage

```bash
# List available templates
mcp-template list

# Deploy a template
mcp-template deploy file-server

# View logs
mcp-template logs file-server

Show Configuration Options

# View configuration options for any template
mcp-template deploy file-server --show-config

# Deploy with custom configuration
mcp-template deploy file-server --config read_only_mode=true

# Deploy with config file
mcp-template deploy file-server --config-file config.json

Available Templates

Our templates are automatically discovered and validated using the TemplateDiscovery utility to ensure only working implementations are listed. This keeps the documentation up-to-date as new templates are added.

Use mcp-template list to see all currently available templates, or visit the Templates section for detailed documentation.

Popular Templates: - file-server - Secure filesystem access for AI assistants - demo - Demonstration server with greeting tools - github - GitHub API integration for repository access - database - Database connectivity for SQL operations

Architecture

The system uses a simple architecture designed for self-hosted deployments:

┌─────────────┐    ┌──────────────────┐    ┌─────────────────────┐
│   CLI Tool  │────│ Template         │────│ Docker Backend      │
│             │    │ Discovery        │    │                     │
│ • Commands  │    │ • Load metadata  │    │ • Container deploy  │
│ • Config    │    │ • Schema validation │  │ • Volume management │
│ • Display   │    │ • Config mapping  │    │ • Health monitoring │
└─────────────┘    └──────────────────┘    └─────────────────────┘

Key Components: - CLI Interface - Rich command-line interface (mcp-template) - Template Discovery - Automatic detection and validation of templates - Docker Backend - Container-based deployment with volume management - Configuration System - Multi-source configuration with type conversion

Configuration System

Templates support flexible configuration from multiple sources:

Configuration precedence (highest to lowest): 1. Environment variables (--env KEY=VALUE) 2. CLI configuration (--config KEY=VALUE) 3. Configuration files (--config-file config.json) 4. Template defaults

Example configuration:

# Using CLI options
mcp-template deploy file-server \
  --config read_only_mode=true \
  --config max_file_size=50 \
  --config log_level=debug

# Using environment variables
mcp-template deploy file-server \
  --env MCP_READ_ONLY=true \
  --env MCP_MAX_FILE_SIZE=50

# Using config file
mcp-template deploy file-server --config-file production.json

Template Development

Create custom MCP server templates:

# Interactive template creation
mcp-template create my-custom-server

# Follow prompts to configure:
# - Template metadata
# - Configuration schema
# - Docker setup
# - Documentation

Each template includes: - template.json - Metadata and configuration schema - Dockerfile - Container build instructions - README.md - Template documentation - docs/index.md - Documentation site content - src/ - Implementation code

Documentation

  • Templates - Available templates and their configuration
  • Getting Started - Installation and first deployment
  • Guides - Advanced usage and template development
  • Development - Technical architecture and development

Community

Commercial Services

Need help with custom MCP servers or enterprise deployment?

MCP Platform offers: - Custom MCP server development - Enterprise hosting and support - Professional services and consulting

📧 Contact us: tooling@dataeverything.ai

License

This project is licensed under the MIT License - see the LICENSE file for details.


MCP Server Templates - Deploy AI-connected services on your own infrastructure.