locust-mcp-server
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.
Documentation
🚀 ⚡️ locust-mcp-server
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.
✨ Features
- 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

🔧 Prerequisites
Before you begin, ensure you have the following installed:
- Python 3.13 or higher
- uv package manager (Installation guide)
📦 Installation
1. Clone the repository:
git clone https://github.com/qainsights/locust-mcp-server.git2. Install the required dependencies:
uv pip install -r requirements.txt3. Set up environment variables (optional):
Create a `.env` file 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🚀 Getting Started
1. 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"})2. 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"
]
}
}
}3. 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
📝 API Reference
Run Locust Test
run_locust(
test_file: str,
headless: bool = True,
host: str = "http://localhost:8089",
runtime: str = "10s",
users: int = 3,
spawn_rate: int = 1
)Parameters:
- `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
✨ Use Cases
- LLM powered results analysis
- Effective debugging with the help of LLM
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
Frequently asked questions
What is locust-mcp-server?
locust-mcp-server is 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.
How do I install locust-mcp-server?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is locust-mcp-server open source?
Yes — it is hosted on GitHub at https://github.com/QAInsights/locust-mcp-server and has 9 stars.
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