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cursor-mcp-demo

MCP.Pizza Chef: KelvinQiu802

Cursor-mcp-demo is an MCP client designed to orchestrate and manage real-time context flow between LLMs and MCP servers. It enables seamless integration of structured data and APIs into AI workflows, facilitating multi-step reasoning and interaction across diverse environments. This client supports building AI applications that leverage the Model Context Protocol for enhanced context awareness and tool interoperability.

Use This MCP client To

Manage context flow between LLMs and MCP servers Coordinate multi-step reasoning in AI workflows Integrate diverse data sources into AI applications Enable real-time interaction with external APIs Facilitate switching between different LLM providers Orchestrate tool usage within AI-enhanced workflows

README

Cursor + Model Context Protocol

阅读

https://www.anthropic.com/news/model-context-protocol

https://modelcontextprotocol.io/introduction

https://docs.cursor.com/context/model-context-protocol

https://github.com/modelcontextprotocol/typescript-sdk

思路

  1. 学习LangGPT仓库，创建一个LangGPT助手
  2. 让LangGPT助手生成一个MCP专家 （学习MCP的文档）
  3. 让MCP专家帮我们实现一个简单的MCP应用

https://github.com/langgptai/LangGPT

案例1: 官方demo

https://github.com/modelcontextprotocol/quickstart-resources/tree/main/weather-server-typescript

案例2: HackerNews接口

https://news.ycombinator.com/

https://github.com/HackerNews/API

https://github.com/pskill9/hn-server

案例3: Dify应用

https://cloud.dify.ai/app/79ff8bc4-1cfe-4a8f-af67-b10adbc725f5/configuration

扩展

https://github.com/modelcontextprotocol/servers

cursor-mcp-demo FAQ

How does cursor-mcp-demo handle context management?
It orchestrates real-time context flow between LLMs and MCP servers to maintain up-to-date environment awareness.
Can cursor-mcp-demo work with multiple LLM providers?
Yes, it supports provider-agnostic interfaces, enabling use with OpenAI, Anthropic Claude, and Google Gemini.
What programming languages is cursor-mcp-demo compatible with?
It is built with TypeScript and integrates well with JavaScript/TypeScript environments.
How does cursor-mcp-demo improve AI workflow development?
By managing context and tool orchestration, it simplifies building complex, multi-step AI applications.
Is cursor-mcp-demo suitable for production environments?
Yes, it is designed for robust, real-time context management in production-grade AI systems.
Does cursor-mcp-demo support integration with external APIs?
Yes, it facilitates real-time interaction with various external data sources and APIs.
How can I extend cursor-mcp-demo for custom use cases?
Its modular architecture allows adding new MCP servers and tools to tailor workflows.
Where can I find example implementations for cursor-mcp-demo?
Official demos and community projects like LangGPT and HackerNews MCP servers provide practical examples.