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MCP Server

@devhysterical

Repository

Basic information

Category

Other

Transports

stdio

Author

devhysterical

About MCP Server

No overview available yet

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

MCP Server config

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

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

MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

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

Frequently asked questions

1

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.

2

What are the system requirements?

Python 3.8 or above and the pip package manager.

3

How do I run the server?

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

4

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.

5

Where can I view the API documentation?

Access `http://localhost:8000/docs` to see the auto-generated Swagger UI documentation.

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