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Containerlab MCP Server

by FloSch62

This is a Model Context Protocol (MCP) server designed for interacting with containerlab using AI, specifically tailored for Claude desktop. It enables Claude to manage and interact with containerlab environments using natural language.

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What is Containerlab MCP Server?

The Containerlab MCP Server is a tool that allows AI models like Claude to interact with and manage containerlab environments. It acts as a bridge, translating natural language commands into actions within containerlab.

How to use Containerlab MCP Server?

  1. Build the MCP server executable for your operating system (Windows, Mac, or Linux). 2. Place the executable in an accessible location. 3. Create a claude_desktop_config.json file with the correct path to the executable and the containerlab API server URL. 4. Ensure the containerlab API server is running. 5. Configure Claude Desktop to use the MCP server.

Key features of Containerlab MCP Server

  • Natural language interaction with containerlab

  • Deployment of network topologies via AI

  • Inspection of lab details

  • Execution of commands on lab nodes

  • Lab destruction and cleanup

Use cases of Containerlab MCP Server

  • Automated network topology deployment

  • AI-powered network troubleshooting

  • Simplified containerlab management

  • Rapid prototyping of network configurations

  • Learning and experimenting with network technologies

FAQ from Containerlab MCP Server

What is containerlab?

Containerlab is a tool for deploying and managing container-based network topologies.

What is MCP?

MCP stands for Model Context Protocol, which allows AI models to interact with external systems.

What is Claude Desktop?

Claude Desktop is an AI assistant that can be used to interact with the MCP server.

Where can I find the containerlab API server?

The containerlab API server is available at https://github.com/srl-labs/clab-api-server.

What if my containerlab API server is not running on localhost:8080?

Update the API_SERVER_URL in the claude_desktop_config.json file to the correct URL.