Gemini Search
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
What is Gemini Search?
Gemini Search is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to 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
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
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Model Context Protocol (MCP) with Gemini 2.5 Pro. Convert co
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx mcp-gemini-searchConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Gemini Search
The mcp-gemini-search server demonstrates how to combine Gemini 2.5 Pro's function-calling capability with the Model Context Protocol to convert natural-language travel queries into structured flight searches. It uses SerpAPI's Google Flights integration as the data source and Gemini to extract flight parameters (origin, destination, date) from conversational input, returning JSON-formatted flight results. Developers exploring AI agent architectures, function-calling patterns, or travel-tech integrations will find this server a practical reference implementation for chaining LLM reasoning with MCP tool execution.
Prerequisites
- Python 3.10 or later and pip installed
- A Google Gemini API key (GEMINI_API_KEY) — obtain from Google AI Studio at aistudio.google.com
- A SerpAPI key (SERP_API_KEY) — obtain from serpapi.com
- An MCP client such as Claude Desktop, or the ability to run the provided client.py script directly
Clone the repository
Clone the mcp-gemini-search repository to your local machine to get the server and client scripts.
git clone https://github.com/arjunprabhulal/mcp-gemini-search
cd mcp-gemini-searchInstall dependencies
Install the required Python packages including the MCP flight search library and its dependencies.
pip install -r requirements.txt
pip install mcp-flight-searchSet environment variables
Export your Gemini and SerpAPI keys. Both are required — Gemini handles natural language understanding and parameter extraction; SerpAPI fetches actual flight data from Google Flights.
export GEMINI_API_KEY=your_gemini_api_key_here
export SERP_API_KEY=your_serpapi_key_hereRun the MCP server
Start the MCP flight search server. By default it runs over STDIO and is ready to accept queries from client.py or any MCP-compatible client.
python server.pySend a flight search query
Use the included client script to send a natural-language flight query. Gemini will extract the parameters and the MCP tool will return structured results.
python client.py
# When prompted, enter: Find flights from Atlanta to Las Vegas on 2025-05-05Gemini Search Examples
Client configuration
Configure Claude Desktop to launch the mcp-gemini-search server as a local STDIO process. Replace the path and API keys with your own values.
{
"mcpServers": {
"gemini-flight-search": {
"command": "python",
"args": ["/path/to/mcp-gemini-search/server.py"],
"env": {
"GEMINI_API_KEY": "your_gemini_api_key_here",
"SERP_API_KEY": "your_serpapi_key_here"
}
}
}
}Prompts to try
These natural-language queries demonstrate Gemini's parameter extraction feeding into the MCP flight search tool.
- "Find flights from Atlanta to Las Vegas on 2025-05-05"
- "Find flights from Atlanta to Las Vegas tomorrow"
- "What are the cheapest direct flights from New York to Chicago next Monday?"
- "Show me morning flights from Los Angeles to Seattle on 2025-06-15"Troubleshooting Gemini Search
GEMINI_API_KEY or SERP_API_KEY environment variable not found
Export both variables in the same shell session before running server.py, or add them to the env block in your MCP client configuration. Confirm with: echo $GEMINI_API_KEY.
SerpAPI returns no results or quota exceeded error
Check your SerpAPI account at serpapi.com to confirm remaining credits. Free accounts have limited monthly searches. Ensure SERP_API_KEY is valid and not expired.
Gemini fails to extract flight parameters from the query
Use explicit city names and ISO date formats (YYYY-MM-DD) in your queries. Gemini function calling works best with unambiguous origin, destination, and date values rather than relative terms like 'next week'.
Frequently Asked Questions about Gemini Search
What is Gemini Search?
Gemini Search is a Model Context Protocol (MCP) server that 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 It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Gemini Search?
Follow the installation instructions on the Gemini Search GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Gemini Search?
Gemini Search works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Gemini Search free to use?
Yes, Gemini Search is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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