What is Multiplemcpserverwithpythonhost

multipleMCPServerWithPythonHost is a Python implementation of a Server-Sent Events (SSE) Model Control Protocol (MCP) host that can run multiple MCP servers simultaneously, utilizing Google’s Gemini API.

Use cases

Use cases include integrating Google Calendar functionalities into applications, managing multiple data streams from various MCP servers, and developing real-time applications that require efficient data handling.

How to use

To use multipleMCPServerWithPythonHost, clone the repository, create a .env file with your API keys, set up the Google Calendar API, update the config.json file with the desired MCP servers, and run the application using the provided commands.

Key features

Key features include the ability to run multiple MCP servers, support for SSE protocol, configuration through JSON files, and the option to package the host app for distribution.

Where to use

multipleMCPServerWithPythonHost can be used in fields such as web development, real-time data processing, and applications that require server-client communication through SSE.

Multiple MCP SSE Servers with a Python Host

This repository contains a Server-Sent Events (SSE) Model Control Protocol (MCP) client implementation that uses Google’s Gemini API.
The Host app reads the config.json file, instantiates instances of MCP Client class to launch the MCP servers and maintain connections with them, clean up on shutdown etc.

It’s possible to package this host app as a dmg package and distribute which can then be used with any MCP SSE ervers.
Todo: Add stdio server support
Todo: Add multiple model support
Todo: Add tool chaining

Setup

1. Clone this repository:

   git clone https://github.com/hackerinheels/multipleMCPServerWithPythonHost.git
   cd multipleMCPServerWithPythonHost
   

2. Create a .env file in the root directory with your API keys:

   GEMINI_API_KEY=your_api_key_here
   MODEL_NAME=gemini-2.0-flash
   

   You can get a Gemini API key from Google’s AI Studio.

3. Set up Google Calendar API using the instructions in the googleCalendar/README.md file

4. Update config.json to include the browser-use server:

   {
     "mcpServers": {
       "calendar": {
         "command": "uv",
         "args": [
           "run",
           "googleCalendar/calendarServer.py",
           "--port",
           "8000"
         ]
       },
       "browser-use": {
         "command": "uv",
         "args": [
           "run",
           "<path-to-browser-use-mcp-server>/server",
           "--port",
           "8006"
         ]
       }
     }
   }
   

   Replace <path-to-browser-use-mcp-server> with the actual path where you cloned the repository.

5. Create a .env file in the browser-use-mcp-server directory with the following configuration:

CHROME_PATH="/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"

Running the Application

uv venv --python 3.11
source .venv/bin/activate
uv pip install -r requirements.txt
uv run host.py

This will start all the servers listed in the config.json file

Usage

Once the servers and client are running, you can interact with them by typing queries.

Google Calendar Commands

The calendar server provides the following tools:

• list_events: List upcoming calendar events
• get_event_details: Get detailed information about a specific event
• search_events: Search for events matching a query

Example queries:

• “Show my upcoming events”
• “Search for meetings with John”
• “Get details for event {event_id}”

Browser Use For Browser Automation

This tool enable browser automation and control with the following tools:

• ‘browser_use’
• ‘browser_get_result’

Type quit to exit the client.

Requirements

• Python 3.11+
• UV package manager
• Google Gemini API key
• Google Calendar API credentials (for calendar server)

License

MIT

MCP Multi-Server Configuration

This repository demonstrates how to load and run multiple MCP servers using a configuration file.

Servers Included

Calendar Server

• Interact with Google Calendar
• Manage events and schedules

Browser-use Server

• Automate browser interactions
• Control Chrome browser programmatically
• Execute browser-based tasks

4. Browser-use Server Environment Setup

Create a .env file in the browser-use-mcp-server directory with the following configuration:

CHROME_PATH="/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"

Note: Make sure to replace “your-openai-api-key” with your actual OpenAI API key.

Notes

• Make sure all API keys are properly configured in .env
• Ensure Chrome is installed for browser-use server
• Each server runs on its designated port
• The host manages all server lifecycles

Troubleshooting

• If a server fails to start, check its port availability
• Verify all environment variables are set correctly
• Ensure Chrome path is correct for your system