Gemini Function Calling + Model Context Protocol(MCP) Flight Search
What is Gemini Function Calling + Model Context Protocol (MCP) Flight Search?
Gemini Function Calling + MCP Flight Search is a natural language flight search system that utilizes Google's Gemini LLM and Model Context Protocol (MCP) to convert conversational queries into flight searches.
How to use the project?
To use this project, clone the repository, install the required dependencies, set up your environment variables with your API keys, and run the client script to start searching for flights using natural language queries.
Key features of the project?
- Natural language flight search using Gemini API
- Automatic parameter extraction via function calling
- Integration with
mcp-flight-searchtool via stdio - Formatted JSON output of flight results
- Environment-based configuration for API keys
Use cases of the project?
- Finding flights based on natural language queries (e.g., "Find flights from New York to London on June 10")
- Integrating flight search capabilities into applications using AI
- Automating flight search processes for travel agencies
FAQ from the project?
- What are the prerequisites for running this project?
You need Python 3.7+, a Google AI Studio API key for Gemini, a SerpAPI key, and the
mcp-flight-searchpackage installed.
- How does the project handle errors?
The integration includes error handling for input validation, API communication errors, tool execution failures, and response parsing issues.
- Is there a demo available?
Yes, you can see example outputs in the project documentation.