🚀 MCP Gemini Search

Welcome to the MCP Gemini Search repository! This project focuses on utilizing the Model Context Protocol (MCP) alongside Gemini 2.5 Pro. It converts conversational queries into flight searches, leveraging Gemini's function calling capabilities and MCP's flight search tools.

Table of Contents

1. Introduction
2. Features
3. Installation
4. Usage
5. Contributing
6. License
7. Contact

Introduction

The MCP Gemini Search project aims to bridge the gap between conversational AI and practical flight search functionalities. With the rise of AI-driven applications, it becomes essential to streamline the user experience. This project makes it easy to convert natural language queries into actionable flight searches, providing users with quick and accurate results.

Features

• Conversational Queries: Users can input flight searches in natural language.
• Function Calling: Utilizes Gemini’s function calling capabilities to execute flight searches efficiently.
• Integration with MCP: Leverages the Model Context Protocol for enhanced flight search tools.
• Real-Time Results: Provides up-to-date flight information and options.
• User-Friendly Interface: Designed for ease of use, making it accessible to all users.

Installation

To get started with MCP Gemini Search, follow these steps:

1. Clone the repository:

   git clone https://github.com/long230912/mcp-gemini-search.git
   

2. Navigate into the project directory:

   cd mcp-gemini-search
   

3. Install the necessary dependencies. You can use pip or your preferred package manager:

   pip install -r requirements.txt
   

4. Download and execute the latest release from our Releases section.

Usage

Once you have installed the project, you can start using it. Here’s a simple guide to get you started:

1. Launch the Application:

   python main.py
   

2. Input a Query: Type in your flight search query in natural language, such as "Find me a flight from New York to Los Angeles next week."

3. Receive Results: The application will process your request and return a list of available flights based on your query.

4. Explore Options: You can refine your search by specifying dates, times, and other preferences.

Contributing

We welcome contributions to improve MCP Gemini Search. If you would like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them with clear messages.
4. Push your changes to your forked repository.
5. Create a pull request to the main repository.

Please ensure that your code adheres to our coding standards and includes tests where applicable.

License

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

Contact

For any questions or feedback, please reach out to the project maintainers:

• Maintainer Name: Long
• Email: long230912@example.com
• GitHub: long230912

Acknowledgments

• Thanks to the developers of the Model Context Protocol and Gemini for their contributions to AI and flight search technology.
• Special thanks to the open-source community for their continuous support and collaboration.

Conclusion

MCP Gemini Search offers a unique solution for transforming conversational queries into flight searches. With its robust features and user-friendly interface, it aims to enhance the travel planning experience. We invite you to explore the project, contribute, and provide feedback.

For the latest updates and releases, check out our Releases section.