Gemini MCP Integration

Guide for integrating Google’s Gemini models with PraisonAI agents using MCP

Add Gemini Tool to AI Agent

Quick Start

1. Set API Key

   Set your Google API key as an environment variable in your terminal:

   export GOOGLE_API_KEY=your_google_api_key_here
   
2. Create a file

   Create a new file gemini_airbnb.py with the following code:

   from praisonaiagents import Agent, MCP
   import os
   
   # Get API key from environment variable
   google_api_key = os.environ.get("GOOGLE_API_KEY")
   
   search_agent = Agent(
       instructions="""You help book apartments on Airbnb.""",
       llm="gemini/gemini-2.5-pro-exp-03-25",
       tools=MCP(
           command="npx",
           args=["-y", "@openbnb/mcp-server-airbnb", "--ignore-robots-txt"],
           env={"GOOGLE_API_KEY": google_api_key}
       )
   )
   
   search_agent.start("MUST USE airbnb_search Tool to Search. Search for Apartments in Paris for 2 nights. 04/28 - 04/30 for 2 adults. All Your Preference")
   
3. Install Dependencies

   Make sure you have Node.js installed, as the MCP server requires it:

   pip install "praisonaiagents[llm]"
   
4. Run the Agent

   Execute your script:

   python gemini_airbnb.py
   

Requirements

• Python 3.10 or higher
• Node.js installed on your system
• Google API key for Gemini models

Features

Gemini 2.5 Pro

Leverage Google’s advanced Gemini 2.5 Pro model.

MCP Integration

Seamless integration with Model Context Protocol.

Airbnb Search

Search for accommodations on Airbnb with natural language queries.

Environment Variables

Securely pass API keys using environment variables.