A Model Context Protocol (MCP) server implementation for running Locust load tests. This server enables seamless integration of Locust load testing capabilities with AI-powered development environments. It exposes a simple toolchain to start and monitor Locust tests from MCP clients, supporting both headless operation and Locust's UI. Users can configure test parameters such as the number of concurrent users, spawn rate, and test duration, and specify the target host. The server is designed to be invoked via the run_locust function, which accepts test_file, headless, host, runtime, users, and spawn_rate. An MCP client can register the server in a mcpServers spec, enabling commands like run locust test for hello.py. Real-time test execution output is available, and HTTP/HTTPS is supported out of the box for remote control and result collection. The project also supports custom task scenarios and is intended to integrate with MCP-enabled development workflows and LLM-powered result analysis.