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MCP Server Example Ki7
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MCP Server Example Ki7

A conversational AI agent based on the MCP protocol, Express.js, and the Gemini API, supporting automated Twitter posting and dynamic interactions.
Artificial intelligence chatbotsSocial media#AI Agent#Twitter Automation#MCP Service#Real - Time Interaction.JavaScript
2 points
7

What is the AI Agent with MCP Server & Gemini API?

This is an intelligent conversational agent system that combines the structured tool interaction capabilities of the MCP server, the backend services of Express.js, and the advanced language understanding capabilities of the Gemini API. It can automate various tasks such as Twitter posting.

How to use the AI Agent?

Users only need to send natural language requests, and the system will automatically parse and execute the corresponding operations, such as posting tweets or performing mathematical calculations. It supports real - time communication via HTTP API or SSE.

Use Cases

Suitable for scenarios that require automated social media management, intelligent customer service, dynamic calculations, etc. It is especially suitable for developers who need to integrate AI capabilities into existing systems.

Main Features

MCP Server IntegrationProvides a structured tool interaction framework that enables AI to understand and execute specific tasks
Express.js BackendPowerful API endpoint support, providing SSE and HTTP message processing capabilities
Gemini AI IntegrationUtilizes the advanced language understanding capabilities of the Google Gemini API to generate dynamic responses
Twitter (X) AutomationPosts tweets directly to the Twitter platform through the createPost tool
Real - Time Communication (SSE)Uses Server - Sent Events (SSE) to achieve real - time push of AI responses

Advantages and Limitations

Advantages
One - stop solution: Integrates AI inference, task execution, and API calls
Flexible and scalable: New tools and functions can be easily added
Real - time interaction: Achieves a smooth user experience through SSE
Powerful language understanding: Handles complex requests with the help of the Gemini API
Limitations
Requires Twitter API permissions to use the posting function
Depends on the service availability of the Google Gemini API
Requires basic programming knowledge for advanced customization

How to Use

Send a Request
Send natural language instructions to the server via an HTTP request or an SSE connection
Process the Request
The MCP server will parse the request and call the corresponding tools for processing
Get the Response
Receive the processing results via an SSE stream or an HTTP response

Usage Examples

Automated Tweet PostingThe system can automatically convert user requests into tweets and post them
Dynamic CalculationProcess mathematical calculation requests and return the results
Intelligent ConversationConduct conversations based on the natural language understanding capabilities of the Gemini API

Frequently Asked Questions

How to obtain Twitter API access permissions?
What are the advantages of an SSE connection?
Can custom tools be added?

Related Resources

Model Context Protocol Documentation
Official technical documentation for the MCP protocol
Gemini API Reference
Official documentation for the Google Gemini API
Express.js Guide
Official documentation for the Express.js framework
Project GitHub Repository
Source code repository for this 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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