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mcp-server-templates

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A flexible platform that provides Docker & Kubernetes backends, a lightweight CLI (mcpt), and client utilities for seamless MCP integration. Spin up servers from templates, route requests through a single endpoint with load balancing, and support both deployed (HTTP) and local (stdio) transports — all with sensible defaults and YAML-based configs.

7 stars PythonAI & Machine Learning Updated Aug 29, 2025
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Documentation

🚀 This Project Has Moved!

> ## ⚠️ **IMPORTANT: This repository has been renamed and moved to MCP Platform**

>

> What changed:

> - New Repository: `Data-Everything/MCP-Platform`

> - New Package: `pip install mcp-platform` (replaces `mcp-templates`)

> - New CLI: `mcpp` command (replaces `mcpt`)

> - Enhanced Features: Improved architecture and expanded capabilities

>

> Migration is easy:

> ```bash

> # Uninstall old package

> pip uninstall mcp-templates

>

> # Install new package

> pip install mcp-platform

>

> # Use new command (all your configs work the same!)

> mcpp deploy demo # instead of mcpt deploy demo

> ```

>

> **📚 Complete Migration Guide | 🆕 New Documentation**


MCP Server Templates (Legacy)

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

Version
Python Versions
License
Discord

> 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.


🚀 Quick Start

bash
# Install MCP Templates
pip install mcp-templates

# List available templates
mcpt list

# Deploy instantly
mcpt deploy demo

# View deployment
mcpt logs demo

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


⚡ Why MCP Templates?

Traditional MCP SetupWith MCP Templates
❌ Complex configuration✅ One-command deployment
❌ Docker expertise required✅ Zero configuration needed
❌ Manual tool discovery✅ Automatic detection
❌ Environment setup headaches✅ Pre-built containers

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


🌟 Key Features

🖱️ One-Click Deployment

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

🔍 Smart Tool Discovery

Automatically finds and showcases every tool your server offers.

🧠 Intelligent Caching

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

💻 Powerful CLI

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

🛠️ Flexible Configuration

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

📦 Growing Template Library

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


📚 Installation

bash
pip install mcp-templates

Docker

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

From Source

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

🎯 Common Use Cases

Deploy with Custom Configuration

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

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

Manage Deployments

bash
# List all deployments
mcpt list --deployed

# Stop a deployment
mcpt stop demo

# View logs
mcpt logs demo --follow

Template Development

bash
# Create new template
mcpt create my-template

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

🏗️ Architecture

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

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


📦 Available Templates

TemplateDescriptionTransportUse Case
demoHello world MCP serverHTTP, stdioTesting & learning
filesystemSecure file operationsstdioFile management
gitlabGitLab API integrationstdioCI/CD workflows
githubGitHub API integrationstdioDevelopment workflows
zendeskCustomer support toolsHTTP, stdioSupport automation

View all templates →


🛠️ Configuration Examples

Basic Configuration

bash
mcpt deploy filesystem --config allowed_dirs="/home/user/data"

Advanced Configuration

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

Configuration File

json
{
  "allowed_dirs": "/home/user/projects",
  "log_level": "DEBUG",
  "security": {
    "read_only": false,
    "max_file_size": "100MB"
  }
}
bash
mcpt deploy filesystem --config-file myconfig.json

🔧 Template Development

Creating Templates

1. Use the generator:

bash
mcpt create my-template

2. Define template.json:

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:

bash
mcpt deploy my-template --backend mock

Full template development guide →


� Migration to MCP Platform

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

Why We Moved

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

What Stays the Same

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

Migration Steps

1. Install new package:

bash
pip uninstall mcp-templates
   pip install mcp-platform

2. Update commands:

bash
# Old command
   mcpt deploy demo

   # New command (everything else identical)
   mcpp deploy demo

3. Update documentation bookmarks:

    Support Timeline

    • 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 →**


    �📖 Documentation (Legacy)


    🤝 Community


    📝 License

    This project is licensed under the Elastic License 2.0.


    🙏 Acknowledgments

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

    Frequently asked questions

    What is mcp-server-templates?

    mcp-server-templates is A flexible platform that provides Docker & Kubernetes backends, a lightweight CLI (mcpt), and client utilities for seamless MCP integration. Spin up servers from templates, route requests through a single endpoint with load balancing, and support both deployed (HTTP) and local (stdio) transports — all with sensible defaults and YAML-based configs.

    How do I install mcp-server-templates?

    Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

    Is mcp-server-templates open source?

    Yes — it is hosted on GitHub at https://github.com/Data-Everything/mcp-server-templates and has 7 stars.

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