Ops Mcp Server
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
- Author
- Heht571
- GitHub stars
- 58
- Downloads
- 386
- Categories
- Other
Jump to
- Real-time CPU, memory, disk, and process monitoring
- Docker container, image, and volume management
- Multi-vendor network device support (Cisco, Huawei, H3C)
- Security vulnerability scans (SSH login, firewall)
- Log analysis and configuration backup
- Extensible plugin architecture with batch operations
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:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Ops Mcp ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install Python 3.10+ and the uv package manager, then clone the project, create a virtual environment, and install dependencies. Deploy via SSE remote mode (uv or Docker Compose) or configure as a local stdio MCP server. An interactive client is available for natural language queries.
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": []
}
}ops-mcp-server
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_
📌 Interactive Client Demo
_On Terminal_
---
⚙️ 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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