Gemini API with MCP Tool Integration
by hitechdk
This project integrates the Google Gemini API with custom tools managed by the MCP framework. It leverages Gemini to process natural language queries and MCP tools to execute actions based on intent.
Last updated: N/A
What is Gemini API with MCP Tool Integration?
This project demonstrates how to integrate the Google Gemini API with custom tools managed by the MCP (Multi-Cloud Platform) framework. It uses the Gemini API to process natural language queries, and leverages MCP tools to execute specific actions based on the query's intent.
How to use Gemini API with MCP Tool Integration?
To use this project, clone the repository, set up a virtual environment, install dependencies using uv, configure the .env file with necessary API keys and paths, and then run the application using python main.py.
Key features of Gemini API with MCP Tool Integration
Integrates Gemini API with MCP tools
Processes natural language queries
Executes actions based on query intent
Customizable prompt and behavior
Use cases of Gemini API with MCP Tool Integration
Automating tasks using natural language
Integrating AI with cloud platforms
Building intelligent agents that interact with external tools
Creating conversational interfaces for cloud management
FAQ from Gemini API with MCP Tool Integration
What is the purpose of this project?
What is the purpose of this project?
To demonstrate how to integrate the Google Gemini API with custom tools managed by the MCP framework.
What are the prerequisites for running this project?
What are the prerequisites for running this project?
Python 3.7+, a Google Cloud project with Gemini API enabled, an MCP environment, and a .env file with API keys and paths.
How do I install the required dependencies?
How do I install the required dependencies?
Use uv pip install dotenv google-generativeai mcp and uv add "mcp[cli]" httpx.
How do I run the application?
How do I run the application?
Execute the command python main.py.
How can I customize the prompt or behavior?
How can I customize the prompt or behavior?
Modify the prompt variable, adjust the get_contents() function, or extend process_response().