Ops Mcp Server

by Heht571

58 386 downloads Not rated yet MIT
GitHub

About

ops-mcp-server is an AI-driven IT operations platform that fuses LLMs and MCP architecture to enable intelligent monitoring, anomaly detection, and natural language interaction with IT infrastructure, with enterprise-grade security and scalability.

Details

License
MIT

Explore

- Extensible plugin architecture.
- Batch operations across multiple devices.
- Tool listing and descriptive commands.

---

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Ops Mcp Server
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Ensure you have Python 3.10+ installed. This project uses uv for dependency and environment management.

curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv .venv

source .venv/bin/activate # Linux/macOS
.\.venv\Scripts\activate # Windows

uv pip install -r requirements.txt

> Dependencies are managed via pyproject.toml.

---

cd server_monitor_sse

pip install -r requirements.txt

Ensure Docker and Docker Compose are installed.

bash
cd server_monitor_sse
docker compose up -d

Add this configuration to your MCP settings:

{
  "ops-mcp-server": {
    "command": "uv",
    "args": [
      "--directory", "YOUR_PROJECT_PATH_HERE",
      "run", "server_monitor.py"
    ],
    "env": {},
    "disabled": true,
    "autoApprove": ["list_available_tools"]
  },
  "network_tools": {
    "command": "uv",
    "args": [
      "--directory", "YOUR_PROJECT_PATH_HERE",
      "run", "network_tools.py"
    ],
    "env": {},
    "disabled": false,
    "autoApprove": []
  },
}

> Note: Replace YOUR_PROJECT_PATH_HERE with your project's actual path.

---

An interactive client (client.py) allows you to interact with MCP services using natural language.

uv pip install openai rich

Edit these configurations within client.py:

```python

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "ops mcp server": {
            "ops-mcp-server": {
                "command": "uv",
                "args": [
                    "--directory",
                    "YOUR_PROJECT_PATH_HERE",
                    "run",
                    "server_monitor.py"
                ],
                "env": []
            }
        }
    }
}

McpServers

{
    "ops-mcp-server": {
        "command": "uv",
        "args": [
            "--directory",
            "YOUR_PROJECT_PATH_HERE",
            "run",
            "server_monitor.py"
        ],
        "env": []
    }
}

中文

ops-mcp-server: an AI-driven IT operations platform that fuses LLMs and MCP architecture to enable intelligent monitoring, anomaly detection, and natural human-infrastructure interaction with enterprise-grade security and scalability.

---

📖 Table of Contents

- Project Overview
- Key Features
- Demo Videos
- Installation
- Deployment
- Local MCP Server Configuration
- Interactive Client Usage
- License
- Notes

---

🚀 Project Overview

ops-mcp-server is an IT operations management solution for the AI era. It achieves intelligent IT operations through the seamless integration of the Model Context Protocol (MCP) and Large Language Models (LLMs). By leveraging the power of LLMs and MCP's distributed architecture, it transforms traditional IT operations into an AI-driven experience, enabling automated server monitoring, intelligent anomaly detection, and context-aware troubleshooting. The system acts as a bridge between human operators and complex IT infrastructure, providing natural language interaction for tasks ranging from routine maintenance to complex problem diagnosis, while maintaining enterprise-grade security and scalability.

---

🌟 Key Features

🖥️ Server Monitoring

- Real-time CPU, memory, disk inspections.
- System load and process monitoring.
- Service and network interface checks.
- Log analysis and configuration backup.
- Security vulnerability scans (SSH login, firewall status).
- Detailed OS information retrieval.

📦 Container Management (Docker)

- Container, image, and volume management.
- Container resource usage monitoring.
- Log retrieval and health checks.

🌐 Network Device Management

- Multi-vendor support (Cisco, Huawei, H3C).
- Switch port, VLAN, and router route checks.
- ACL security configuration analysis.
- Optical module and device performance monitoring.

➕ Additional Capabilities

- Extensible plugin architecture.
- Batch operations across multiple devices.
- Tool listing and descriptive commands.

---

🎬 Demo Videos

📌 Project Demo

_On Cherry Studio_

Demo Animation

📌 Interactive Client Demo

_On Terminal_

Client Demo Animation

---

⚙️ Installation

Ensure you have Python 3.10+ installed. This project uses uv for dependency and environment management.

1. Install UV

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Set Up Virtual Environment

```bash
uv venv .venv

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