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gatling-mcp-server

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gatling-mcp-server

Build

A FastAPI MCP (Model Context Protocol) server built with FastMCP. Exposes gatling-server's task API as MCP tools over streamable-http transport, so an AI agent can upload a jar, submit a Gatling simulation, poll its status, and pull back logs - without anyone hand-writing curl.

This README covers developing gatling-mcp-server. For running, deploying, and connecting clients to it, see the docs site: jecklgamis.github.io/gatling-mcp-server (or browse docs/ directly).

MCP Tools (/gatling_mcp)

Tool

Description

upload_jar

Upload a local jar file to gatling-server; returns an id and a ready-to-use url. Colocated setups only - see Architecture docs

submit_task

Submit a Gatling simulation to run, given a simulation class, jar URL, and javaOpts

get_task_status

Get a task's current status (Started/Completed/Aborted, success, timestamps)

get_console_log

Get the raw JVM/Gatling console output for a task - useful for diagnosing failures

get_simulation_log

Get Gatling's own simulation report for a completed task (binary on recent Gatling versions - prefer get_console_log)

abort_task

Kill a currently running task

Every tool is also mounted as a plain REST route (GET for read-only tools, POST for anything that mutates state), and all routes require the Authorization: Bearer <GATLING_MCP_API_TOKEN> header described below.

Related MCP server: agentic_actions_mcp

Getting Started

Requirements

Configuration

Env Var

Description

Default

GATLING_SERVER_URL

Base URL of the gatling-server instance

http://localhost:58080

GATLING_SERVER_API_TOKEN

Bearer token for gatling-server's /task/* API

default

GATLING_MCP_API_TOKEN

Bearer token required on every request to this server (MCP and REST alike)

default

GATLING_MCP_REQUEST_TIMEOUT

Timeout (seconds) for lightweight calls (submit/status/logs/abort)

30

GATLING_MCP_UPLOAD_TIMEOUT

Timeout (seconds) for upload_jar, which can move tens of MB

300

Run Locally

pip install -r requirements.txt
python server.py

Or ./run-server.sh, which applies the defaults from the table above.

Testing

pytest -s

Documentation

Running Docker/Kubernetes, installing a tagged release, connecting MCP clients (Claude Code, Claude Desktop, Cursor, Windsurf, Cline, Gemini CLI, JetBrains AI Assistant), and the local-vs-remote-deployment/recommended agent workflow rationale all live in the docs site: jecklgamis.github.io/gatling-mcp-server (source in docs/).

This server cannot be deployed

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Maintenance

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