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.

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:

   • Go to the Google Cloud Console
   • Create a new project or select an existing one
   • Enable the Google Calendar API
   • Create OAuth 2.0 credentials
   • Download the credentials and save as credentials.json in the current directory

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

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

Setup Instructions

1. Environment Setup

# Create and activate virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

2. Configuration

Create a .env file with your API keys:

GEMINI_API_KEY="your-gemini-api-key"
MODEL_NAME="gemini-1.5-flash"

3. Browser-use MCP Server Setup

1. Download the server:

   git clone https://github.com/co-browser/browser-use-mcp-server
   

2. 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.

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