About Mcp_server_client_assessment
An MCP client-server system for developers exploring query-driven command execution. The server uses Ollama LLM to generate and run system commands, then returns their output, with FastAPI and FastMCP in the implementation.
Key features
- 01Generate system commands with Ollama LLM
- 02Execute commands and return output
- 03Built with FastAPI and FastMCP
Use cases
- 01Generate and run commands from queries
- 02Test MCP client-server interactions
MCP support
Implements an MCP client-server flow: it receives queries from a client and returns command execution output.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP Client-Server System
Overview
This project implements an MCP-based Client-Server System where a client sends a query, the server processes it using Ollama LLM, generates a system command, executes it, and returns the output. The implementation uses FastAPI, FastMCP, aiohttp, and subprocess for command execution.
Installation
Prerequisites
Python 3.8+
Pip package manager
Ollama installed and running
MCP Python SDK installed
Setup
Clone the repository:
cd mcp_server_client_assessment
Install dependencies:
pip install -r requirements.txt
Start the server:
python server.py
Run the client:
python client.py
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.