MCP Protocol Server
M

MCP Protocol Server

A model context protocol server based on FastAPI, providing model context management, session handling, and real-time communication functions.
2 points
5.2K

What is the Model Context Protocol Server?

The Model Context Protocol (MCP) server is a dedicated service for managing AI model contexts and sessions. It helps developers efficiently maintain model states, handle user sessions, and support real-time communication.

How to use the MCP server?

Interact with the server through simple REST APIs or WebSocket connections to manage model contexts and user sessions. It supports rapid deployment and scaling.

Applicable scenarios

Suitable for AI applications that need to maintain long-term conversation states, multi-round dialogue systems, AI services that require real-time updates, etc.

Main features

Model context management
Provides full lifecycle management for creating, updating, querying, and deleting model contexts
Session handling
Supports the creation, maintenance, and persistent storage of user sessions
Real-time WebSocket support
Enables real-time communication and status updates through WebSocket connections
Authentication and authorization
Built-in security mechanisms to protect API and WebSocket endpoints
Interactive documentation
Built-in Swagger and ReDoc documentation for easy API exploration and testing
Advantages
Built on the high-performance FastAPI framework
Supports both REST and WebSocket communication methods
Complete session management and context maintenance functions
Easy to deploy and scale
Provides detailed interactive API documentation
Limitations
Requires Python environment support
Additional configuration is required for large-scale deployment
Real-time communication functions require WebSocket client support

How to use

Install dependencies
Ensure that Python 3.7+ and pip are installed on the system
Configure the environment
Copy the .env.example file and configure your settings
Start the server
Run the server using uvicorn
Access the API documentation
Open the interactive API documentation in the browser

Usage examples

Create a new session
Initialize a new session for interacting with an AI model
Update the model context
Add new context information to an existing session

Frequently Asked Questions

How to scale the server to support more concurrent users?
What authentication methods are supported?
How is session data persisted?

Related resources

FastAPI official documentation
Learn about the features and characteristics of the underlying framework
GitHub repository
Get the source code and the latest updates
Swagger UI
Interactive API documentation (available after running the service)

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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