Gemini Function Calling + Model Context Protocol(MCP) Flight Search
@arjunprabhulal
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
Overview
What is Gemini Function Calling + Model Context Protocol(MCP) Flight Search?
It is a client demonstration that uses Google’s Gemini 2.5 Pro with function calling to interact with the mcp-flight-search tool via the Model Context Protocol (MCP). It enables natural language flight search queries to be automatically translated into structured function calls and executed against a local MCP server.
How to use Gemini Function Calling + Model Context Protocol(MCP) Flight Search?
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.
Key features of Gemini Function Calling + Model Context Protocol(MCP) Flight Search
- Natural language flight search using Gemini 2.5 Pro
- 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 Gemini Function Calling + Model Context Protocol(MCP) Flight Search
- Searching flights using plain English (e.g., “Find flights from Atlanta
