广告合作
MCP.so
登录

MCP Server Implementation

@yisu201506

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

yisu201506

关于 MCP Server Implementation

Repository for MCP server implementation

#mcp-server#mcp#flask#llm#api

MCP Server Implementation 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-server-yisu201506": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP Server Implementation 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Server Implementation?

A Flask-based implementation of the Model Context Protocol (MCP) that extends Large Language Models with external tools like weather and calculator, using text-based tool invocation directly in the context window.

How to use MCP Server Implementation?

Clone the repository, create a Python virtual environment, install dependencies, set environment variables for API keys, then run flask run or gunicorn app:app. Send chat messages via the POST /chat endpoint with a JSON body containing a messages array.

Key features of MCP Server Implementation

  • Complete MCP parsing, execution, and response handling
  • Sample weather and calculator tools with parameter validation
  • Maintains conversation context across multiple interactions
  • Regex‑based parsing for flexible tool invocation detection
  • Flask REST API for easy chat integration

Use cases of MCP Server Implementation

  • Adding real‑time weather data to an LLM‑powered chatbot
  • Enabling a language model to perform mathematical calculations
  • Building custom tool integrations by inheriting from the Tool base class
  • Demonstrating MCP workflow for educational or prototyping purposes

常见问题

1

What is MCP and how does it differ from function calling?

MCP places tool definitions in the prompt text and parses natural‑language responses for tool calls, while function calling uses structured JSON in API parameters and requires API support.

2

What are the runtime dependencies?

Python 3, Flask, Gunicorn (optional for production), and API keys for the LLM and weather service stored in environment variables.

3

Where is conversation state stored?

The server maintains conversation history across multiple interactions by adding processed responses and tool results back into the message history.

4

What transport does the server use?

HTTP via the Flask development server (default port 5000) or Gunicorn in production.

5

How are tools authenticated?

Weather tool requires a `WEATHER_API_KEY` environment variable; LLM requests require an `LLM_API_KEY`. Both are set in a `.env` file.

评论

其他 分类下的更多 MCP 服务器

N

Next Generation Movers: free moving quotes (remote MCP)

Next Generation Movers

Free moving quotes for AI agents from Next Generation Movers, a licensed interstate mover (USDOT 3764697). US long-distance nationwide and local DC/MD/VA. Indicative ballpark price and booking options; optional $0.01 x40

Maestro

mobile-dev-inc

Painless E2E Automation for Mobile and Web

14.8K

MCP Toolbox for Databases

googleapis

MCP Toolbox for Databases is an open source MCP server for databases.

15.9K

FastMCP v2 🚀

jlowin

🚀 The fast, Pythonic way to build MCP servers and clients.

26.0K

YOUB

Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov

广告合作