MCP Server

Name: MCP Server
Author: devhysterical

@devhysterical

Repository

About MCP Server

No overview available yet

#mcp-server #model-context-protocol #api-server

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP Server?

MCP Server implements the Model Context Protocol (MCP), enabling large language models (LLMs) to interact with external tools and services through a standardized interface.

How to use MCP Server?

Clone the repository, create and activate a Python virtual environment (Python 3.8+), install dependencies with pip install -r requirements.txt, then run python main.py. The server starts at http://localhost:8000. Use its RESTful API endpoints: a GET at / for server info and tool list, or a POST at /execute to invoke tools with JSON parameters.

Key features of MCP Server

Supports multiple tools: calculator, weather, search
RESTful API built with FastAPI
Data validation with Pydantic
Efficient asynchronous processing
Automatic API documentation via Swagger UI at /docs

Use cases of MCP Server

Allow an LLM to perform real-time calculations
Fetch current weather data for a location
Execute web searches through an LLM interface
Extend the server with custom tools for new integrations

FAQ from MCP Server

What is MCP Server?

MCP Server is a server that implements the Model Context Protocol, providing a standardized way for LLMs to use external tools and services.

What are the system requirements?

Python 3.8 or above and the pip package manager.

How do I run the server?

After installing dependencies, run python main.py. The server will be available at http://localhost:8000.

How can I add a new tool?

Add the tool’s name and description to the SUPPORTED_TOOLS dictionary, then add a handler function in process_tool_request and create a dedicated function for the new tool.