Gemini Function Calling + Model Context Protocol(MCP) Flight Search

by arjunprabhulal

56 stars

408 downloads

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GitHub Website

About

Model Context Protocol (MCP) with Gemini 2.5 Pro. Convert conversational queries into flight searches using Gemini's function calling capabilities and MCP's flight search tools

Details

Author: arjunprabhulal
GitHub stars: 56
Downloads: 408
Categories: AI

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Gemini Function Calling + Model Context Protocol(MCP) Flight Search

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

From the repository

Clone the repository, install dependencies (pip install -r requirements.txt and pip install mcp-flight-search), set GEMINI_API_KEY and SERP_API_KEY environment variables, then run python client.py. The client starts the MCP flight search server, sends the user’s natural language query to Gemini, and displays formatted flight results.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "gemini function calling + model context protocol(mcp) flight search": {
            "mcp-gemini-search": {
                "command": "python",
                "args": [
                    "client.py"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-gemini-search": {
        "command": "python",
        "args": [
            "client.py"
        ]
    }
}

Gemini Function Calling + Model Context Protocol(MCP) Flight Search

This project demonstrates how to use Google's Gemini 2.5 Pro with function calling capabilities to interact with the mcp-flight-search tool via Model Context Protocol (MCP). This client implementation shows how to:

1. Connect to a local MCP server process (mcp-flight-search) using stdio communication
2. Use natural language prompts with Gemini 2.5 Pro to search for flights (e.g., "Find flights from Atlanta to Las Vegas on 2025-05-05")
3. Let Gemini automatically determine the correct function parameters from the natural language input
4. Execute the flight search using the MCP tool
5. Display formatted results from the search

Features

Natural language flight search using Gemini 2.5 Pro
Automatic parameter extraction via function calling
Integration with mcp-flight-search tool via stdio
Formatted JSON output of flight results
Environment-based configuration for API keys

Prerequisites

Before running this client, you'll need:

1. Python 3.7+
2. A Google AI Studio API key for Gemini
3. A SerpAPI key (used by the flight search tool)
4. The mcp-flight-search package installed

Dependencies

This project relies on several Python packages:

google-generativeai: Google's official Python library for accessing Gemini 2.5 Pro and other Google AI models.
- Provides the client interface for Gemini 2.5 Pro
- Handles function calling capabilities
- Manages API authentication and requests

mcp-sdk-python: Model Context Protocol (MCP) SDK for Python.
- Provides ClientSession for managing MCP communication
- Includes StdioServerParameters for configuring server processes
- Handles tool registration and invocation

mcp-flight-search: A flight search service built with MCP.
- Implements flight search functionality using SerpAPI
- Provides MCP-compliant tools for flight searches
- Handles both stdio and HTTP communication modes

asyncio: Python's built-in library for writing asynchronous code.
- Manages asynchronous operations and coroutines
- Handles concurrent I/O operations
- Required for MCP client-server communication

json: Python's built-in JSON encoder and decoder.
- Parses flight search results
- Formats output for display
- Handles data serialization/deserialization

Setup

1. Clone the Repository:

    git clone https://github.com/arjunprabhulal/mcp-gemini-search.git

    cd mcp-gemini-search

2. Install Dependencies:

    # Install required Python libraries

    pip install -r requirements.txt

    # Install the MCP flight search tool

    pip install mcp-flight-search

3. Set Environment Variables:

    export GEMINI_API_KEY="YOUR_GEMINI_API_KEY"

    export SERP_API_KEY="YOUR_SERPAPI_API_KEY"

Replace the placeholder values with your actual API keys:
Get your Gemini API key from Google AI Studio
Get your SerpAPI key from SerpApi

Architecture

This project integrates multiple components to enable natural language flight search. Here's how the system works:

Component Interactions

1. User to Client
- User provides natural language query (e.g., "Find flights from Atlanta to Las Vegas tomorrow")
- Client script (client.py) processes the input

2. Client to MCP Server
- Client starts the MCP server process (mcp-flight-search)
- Establishes stdio communication channel
- Retrieves available tools and their descriptions

3. Client to Gemini 2.5 Pro
- Sends the user's query
- Provides tool descriptions for function calling
- Receives structured function call with extracted parameters

4. Client to MCP Tool
- Takes function call parameters from Gemini
- Calls appropriate MCP tool with parameters
- Handles response processing

5. MCP Server to SerpAPI
- MCP server makes requests to SerpAPI
- Queries Google Flights data
- Processes and formats flight information

Data Flow

1. Input Processing

   User Query → Natural Language Text → Gemini 2.5 Pro → Structured Parameters

2. Flight Search

   Parameters → MCP Tool → SerpAPI → Flight Data → JSON Response

3. Result Handling

   JSON Response → Parse → Format → Display to User

Communication Protocols

1. Client ↔ MCP Server
- Uses stdio communication
- Follows MCP protocol for tool registration and calls
- Handles asynchronous operations

2. MCP Server ↔ SerpAPI
- HTTPS requests
- JSON data exchange
- API key authentication

3. Client ↔ Gemini 2.5 Pro
- HTTPS requests
- Function calling protocol
- API key authentication

Error Handling

The integration includes error handling at multiple levels:
- Input validation
- API communication errors
- Tool execution failures
- Response parsing issues
- Data formatting problems

Usage

Run the client:

python client.py

The script will:
1. Start the MCP flight search server process
2. Send your flight search query to 2.5 Pro
3. Use Gemini's function calling to extract search parameters
4. Execute the search via the MCP tool
5. Display the formatted results

Related Projects

This client uses the mcp-flight-search tool, which is available at:
GitHub: arjunprabhulal/mcp-flight-search
PyPI: mcp-flight-search

Author

For more articles on AI/ML and Generative AI, follow me on Medium: @arjun-prabhulal

License

This project is licensed under the MIT License.

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About

Details

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Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Gemini Function Calling + Model Context Protocol(MCP) Flight Search

Features

Prerequisites

Dependencies

Setup

Architecture

Component Interactions

Data Flow

Communication Protocols

Error Handling

Usage

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