🚀 ⚡️ locust-mcp-server
About
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.
Details
- Author
- QAInsights
- GitHub stars
- 13
- Downloads
- 317
- Categories
- Developer Tools, Other
Jump to
- Integrates with the Model Context Protocol framework
- Supports headless and UI modes
- Configurable test parameters (users, spawn rate, runtime)
- HTTP/HTTPS protocol support out of the box
- Real-time test execution output
- Custom task scenarios support
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
🚀 ⚡️ locust-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 3.13+ and uv, clone the repository, install dependencies, and optionally set environment variables. Create a Locust test script, configure the MCP server in your client (e.g., Claude Desktop) using the provided JSON spec, then ask the LLM to run the test. The server provides the run_locust tool for executing tests with configurable options.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"\ud83d\ude80 \u26a1\ufe0f locust-mcp-server": {
"locust-mcp-server": {
"command": "uv",
"args": [
"pip",
"install",
"-r",
"requirements.txt"
]
}
}
}
}McpServers
{
"locust-mcp-server": {
"command": "uv",
"args": [
"pip",
"install",
"-r",
"requirements.txt"
]
}
}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.
- Simple integration with Model Context Protocol framework
- Support for headless and UI modes
- Configurable test parameters (users, spawn rate, runtime)
- Easy-to-use API for running Locust load tests
- Real-time test execution output
- HTTP/HTTPS protocol support out of the box
- Custom task scenarios support
Before you begin, ensure you have the following installed:
- Python 3.13 or higher
- uv package manager (Installation guide)
git clone https://github.com/qainsights/locust-mcp-server.git
- Set up environment variables (optional): Create a.envfile in the project root:
LOCUST_HOST=http://localhost:8089 # Default host for your tests LOCUST_USERS=3 # Default number of users LOCUST_SPAWN_RATE=1 # Default user spawn rate LOCUST_RUN_TIME=10s # Default test duration
- Create a Locust test script (e.g.,hello.py):
from locust import HttpUser, task, between class QuickstartUser(HttpUser): wait_time = between(1, 5) @task def hello_world(self): self.client.get("/hello") self.client.get("/world") @task(3) def view_items(self): for item_id in range(10): self.client.get(f"/item?id={item_id}", name="/item") time.sleep(1) def on_start(self): self.client.post("/login", json={"username":"foo", "password":"bar"})
- Configure the MCP server using the below specs in your favorite MCP client (Claude Desktop, Cursor, Windsurf and more):
{ "mcpServers": { "locust": { "command": "/Users/naveenkumar/.local/bin/uv", "args": [ "--directory", "/Users/naveenkumar/Gits/locust-mcp-server", "run", "locust_server.py" ] } } }
- Now ask the LLM to run the test e.g.run locust test for hello.py. The Locust MCP server will use the following tool to start the test:
- run_locust: Run a test with configurable options for headless mode, host, runtime, users, and spawn rate
run_locust( test_file: str, headless: bool = True, host: str = "http://localhost:8089", runtime: str = "10s", users: int = 3, spawn_rate: int = 1 )
- test_file: Path to your Locust test script
- headless: Run in headless mode (True) or with UI (False)
- host: Target host to load test
- runtime: Test duration (e.g., "30s", "1m", "5m")
- users: Number of concurrent users to simulate
- spawn_rate: Rate at which users are spawned
- LLM powered results analysis
- Effective debugging with the help of LLM
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
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