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A comprehensive Model Context Protocol (MCP) platform providing standardized integrations between AI assistants and various services and APIs. This repository contains both JavaScript and Python implementations of MCP servers and clients for seamless service integration.

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Vanij MCP Platform

License: MIT Node.js Python

A comprehensive Model Context Protocol (MCP) platform providing standardized integrations between AI assistants and various services and APIs. This repository contains both JavaScript and Python implementations of MCP servers and clients for seamless service integration.

📋 Table of Contents

🌟 Overview

The Vanij MCP Platform enables AI assistants to interact with external services through a standardized protocol. It provides a unified interface for connecting to various APIs and services, making it easier to build sophisticated AI-powered applications.

✨ Features

  • Multi-language Support: JavaScript and Python implementations
  • Extensible Architecture: Easy to add new MCP servers
  • Standardized Protocol: Consistent interface across all integrations
  • Production Ready: Built with scalability and reliability in mind
  • Comprehensive Documentation: Detailed guides and API references
  • Testing Tools: Postman collections for easy testing

📁 Project Structure

.
├── mcp_servers/
│   ├── js/                           # JavaScript implementation
│   │   ├── clients/                  # MCP clients
│   │   │   ├── src/
│   │   │   │   ├── client_and_server_config.ts  # Listed MCP Clients & Servers Configurations.
│   │   │   │   └── ...
│   │   │   ├── package.json   
│   │   │   └── ...
│   │   ├── servers/                  # MCP servers
│   │   │   ├── WORDPRESS/           # WordPress integration
│   │   │   ├── ZOOMMCP/             # Zoom integration
│   │   │   ├── SALESFORCE_MCP/      # Salesforce integration
│   │   │   ├── SLACK_MCP/           # Slack integration
│   │   │   └── etc...
│   │   └── package.json
│   └── python/                       # Python implementation
│       ├── clients/                  # MCP clients
│       │   ├── src/
│       │   │   ├── client_and_server_config.py       # Listed MCP Clients & Servers Configurations.
│       │   │   └── ...
│       │   ├── requirements.txt
│       │   └── ...
│       └── servers/                  # MCP servers
│           ├── MCP-GSUITE/          # GSuite integration
│           ├── FACEBOOK_MCP/        # Facebook integration
│           ├── FACEBOOK_ADS_MCP/    # Facebook Ads integration
│           ├── POWER_BI_MCP/        # Power BI integration
│           └── etc ...
├── mcp_servers_documentation/        # Detailed documentation of about MCP servers
├── postman_api_collections/         # API testing collections
└── README.md

🚀 Quick Start

Prerequisites

  • Node.js208+ (for JavaScript implementation)
  • Python 3.8+ (for Python implementation)
  • npm or yarn (for JavaScript dependencies)
  • pip (for Python dependencies)

Choose Your Implementation

  1. JavaScript: Follow the JavaScript Setup guide
  2. Python: Follow the Python Setup guide
  3. Both: Set up both implementations for maximum flexibility

🟨 JavaScript Setup

1. Navigate to JavaScript Directory

cd mcp_servers/js

2. Install Dependencies

npm install

3. Build All Components

npm run build:all

4. Start Development Server

npm run dev:client

5. Available Scripts

  • npm run build:all - Build all clients and servers
  • npm run dev:client - Run client in development mode
  • npm run test - Run test suite
  • npm run lint - Run linting checks

Configuration

JavaScript configuration is managed in:

mcp_servers/js/clients/src/client_and_server_config.ts

🐍 Python Setup

1. Navigate to Python Directory

cd mcp_servers/python/clients

2. Create Virtual Environment

python -m venv venv

3. Activate Virtual Environment

Windows:

venv\Scripts\activate

Unix/MacOS:

source venv/bin/activate

4. Install Dependencies

pip install -r requirements.txt

This command automatically installs all server dependencies as well.

5. Run the Client

python src/main.py

Configuration

Python configuration is managed in:

mcp_servers/python/clients/src/client_and_server_config.py

🔌 Example MCP Servers

JavaScript Implementation

Server Description Status
WordPress Content management and blog operations ✅ Active
Zoom Video conferencing and meeting management ✅ Active
Salesforce CRM and sales automation ✅ Active
Slack Team communication and collaboration ✅ Active
Jira Project management and issue tracking ✅ Active
Google Drive Cloud storage and file management ✅ Active
Zendesk Customer support and ticketing ✅ Active
HubSpot Marketing and CRM platform ✅ Active

Python Implementation

Server Description Status
GSuite Google Workspace integration ✅ Active
Facebook Social media platform integration ✅ Active
Facebook Ads Advertising and campaign management ✅ Active
Power BI Business intelligence and analytics ✅ Active

⚙️ Configuration

JavaScript Configuration

Edit mcp_servers/js/clients/src/client_and_server_config.ts:

export const ServersConfig = [
    {
        server_name :"WORDPRESS", // Server Name should be same as the folder name in mcp_servers/js/servers/ folder.
        server_features_and_capability:`wordpress server is used to create, update, delete and get content from wordpress website.`,
        path : "build/index.js"
    },
    {
        server_name :"User MCP Server Name",   
        server_features_and_capability:`feactures description`,
        path : "dist/index.js" // path should be the build file path in the mcp Server under the folder name
    },
];

Python Configuration

Edit mcp_servers/python/clients/src/client_and_server_config.py:

ServersConfig = [
    {
		"server_name": "MCP-GSUITE",
		"command":"uv",
		"args": [
			"--directory",
			"../servers/MCP-GSUITE/mcp-gsuite",
			"run",
			"mcp-gsuite"
		]
	},
    //other servers...
]

📚 Documentation

Comprehensive documentation for each MCP server is available in the mcp_servers_documentation/ directory:

  • Server-specific setup guides
  • API reference documentation
  • Integration examples
  • Troubleshooting guides

Key Documentation Files

  • mcp_servers_documentation/server_setup.md - General server setup
  • mcp_servers_documentation/api_reference.md - API documentation
  • mcp_servers_documentation/examples/ - Integration examples

🧪 API Collections

The postman_api_collections/ directory contains Postman collections for testing and interacting with MCP servers:

  1. Import collections into Postman
  2. Configure environment variables
  3. Test API endpoints
  4. Validate integrations

🤝 Contributing

We welcome contributions! Please follow these steps:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Development Guidelines

  • Follow existing code style and conventions
  • Add tests for new features
  • Update documentation as needed
  • Ensure all tests pass before submitting PR

📄 License

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

🆘 Support

  • Documentation: Check the mcp_servers_documentation/ directory
  • Issues: Open an issue on GitHub
  • Discussions: Use GitHub Discussions for questions

🏗️ Roadmap

  • Additional language implementations (Go, Rust)
  • More third-party service integrations
  • Enhanced monitoring and logging
  • Docker containerization
  • Kubernetes deployment guides

Built with ❤️ by the Vanij Team

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A comprehensive Model Context Protocol (MCP) platform providing standardized integrations between AI assistants and various services and APIs. This repository contains both JavaScript and Python implementations of MCP servers and clients for seamless service integration.

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