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MCP Gemini
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MCP Gemini

A working demonstration project of the Model Context Protocol (MCP) integrated with Google Gemini, including configuration and operation guides for the server and client.
Artificial intelligence chatbotsEducation and learning tools#Protocol integration#Gemini#Model communication#Demonstration project.Python
2 points
9

What is MCP?

MCP is a protocol for managing the context of AI models. By integrating with Google Gemini, it can more efficiently handle the input, output, and context management of AI models

How to use MCP?

MCP adopts a client - server architecture and can be used after simple setup steps

Use cases

Suitable for applications that need to maintain the AI dialogue context over a long period, such as intelligent customer service and personalized AI assistants

Main features

Real-time context managementRealize real-time context update and synchronization through SSE (Server-Sent Events) technology
Gemini integrationSeamlessly integrate the Google Gemini AI model to provide powerful natural language processing capabilities
Simple APIProvide a concise API interface, which is easy to integrate into existing systems

Advantages and limitations

Advantages
Real-time context update to improve AI response quality
Deep integration with Google Gemini to provide advanced AI capabilities
Lightweight architecture, easy to deploy and maintain
Limitations
A Google API key is required to use Gemini features
Currently only supports the Python environment
The default server configuration may not be suitable for production environments

How to use

Clone the code repository
Clone the project code to the local development environment
Set environment variables
Create a .env file and add your Google API key
Install dependencies
Install all Python dependency packages required by the project
Start the server
Run the SSE server, which listens on port 8080 by default
Start the client
Run the client to connect to the server

Usage examples

Intelligent customer service systemBuild an intelligent customer service that can remember the user's historical conversations
Personalized learning assistantCreate an AI tutor that can track the learning progress

Frequently Asked Questions

How to get a Google API key?
Can the server port be modified?
Which programming languages are supported?

Related resources

Google Gemini documentation
Official Google Gemini development documentation
Introduction to SSE technology
Server-Sent Events technology documentation on MDN
Project GitHub repository
Source code for the MCP Gemini integration project
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
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