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MCP Demo
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MCP Demo

A project demonstrating the MCP protocol, including a server, client, and debugging tool, supporting SSE communication and JWT authentication, and integrating LangChain/LangGraph technology.
Artificial intelligence chatbotsDeveloper tools#MCP Protocol#SSE Communication#Debugging Tools#LangChain.Python
2.5 points
8.5K
Open Site

Overview

Content Details

Alternatives

What is the MCP server?

The MCP server is a backend service that implements the Model Context Protocol, allowing clients to interact with AI models through SSE (Server-Sent Events). It supports basic streaming responses and can also be configured with JWT authentication to protect endpoints.

How to use the MCP server?

You can start the server by running the provided Python script, and then use the client to connect to the SSE endpoint for interaction. It also supports integration with LangChain/LangGraph as an AI model host.

Use cases

Suitable for application scenarios that require real-time AI model interaction, such as chatbots, streaming content generation, AI-assisted tools, etc. Particularly suitable for development projects that require SSE protocol support.

Main Features

SSE Protocol Support
Real-time data stream transmission based on Server-Sent Events
JWT Authentication
Optional security authentication method to protect your endpoints
LangChain Integration
Supports serving as an AI model host for LangChain/LangGraph
Debugging Tools
Provides a dedicated Inspector tool for debugging and testing
Advantages
Lightweight implementation, easy to deploy and integrate
Supports multiple usage methods (direct call/LangChain integration)
Provides visual debugging tools
Open-source project with community support
Limitations
Currently mainly supports the Python ecosystem
The SSE protocol may have compatibility issues in some network environments
Documentation and examples need to be improved

How to Use

Set up the environment
Create a Python virtual environment and install dependencies
Start the server
Choose to start a basic server or a server with JWT authentication
Run the client
Use the example client to connect to the server
LangChain Integration (Optional)
Use the server as an AI model host for LangChain/LangGraph

Usage Examples

Basic Chat Interaction
Implement basic chatbot functions using the SSE protocol
LangChain Integration
Use the MCP server as the AI model backend for LangChain applications
Debugging and Testing
Use the Inspector tool to debug the server response

Frequently Asked Questions

How to enable JWT authentication?
What if the Inspector tool cannot connect to the server?
Which AI models are supported?
How to extend custom functions?

Related Resources

Python SDK Code Repository
Official Python SDK implementation
HTTP Client Example
Example of MCP client implementation
Inspector Tool
Debugging and testing tool for the MCP protocol
Ollama Project
Run large language models locally

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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