Can my agent start a Gatling simulation run via chat?

Yes. Use the 'start_simulation' tool with the specific Simulation ID. The agent will command the Gatling Enterprise infrastructure to begin the load test and return a unique run ID for tracking.

How do I check the request statistics for a completed test run via chat?

Use the 'get_run' tool. Provide the Run ID. Your agent will fetch the full details of the execution, including request stats, error counts, and the virtual user peak reached during the test.

Can I see my credit quotas and team member counts through the agent?

Absolutely. Use the 'list_teams' tool. Your agent will enumerate the teams registered in your Gatling Enterprise account and monitor their member counts and available credit quotas natively.

Gatling MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: Gatling
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Gatling through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Gatling Assistant",
            instructions=(
                "You help users interact with Gatling. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Gatling"
        )
        print(result.final_output)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Gatling MCP Server

Connect your Gatling Enterprise account to any AI agent and take full control of your performance testing and high-scale load simulation through natural conversation.

The OpenAI Agents SDK auto-discovers all 10 tools from Gatling through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Gatling, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Simulation Orchestration — List all Gatling simulations defining load scenarios and retrieve IDs, class names, and team associations natively
Live Test Execution — Trigger new performance test runs on Gatling Enterprise infrastructure and retrieve unique run IDs flawlessly
Test Run Monitoring — Track execution progress, statuses, and peak virtual user (VU) counts for ongoing or completed simulations synchronously
Detailed Stats Retrieval — Access full run details including request statistics, error counts, and injection start/end times limitlessly
Team & Quota Oversight — Enumerate teams registered in Gatling Enterprise and monitor member counts and credit quotas securely
Artifact Management — List uploaded test packages and artifacts to verify versions and upload timestamps across your environment
Resource Pool Auditing — Retrieve the list of load generator pools, identifying regions and instance counts to verify scaling capacity
Autonomous Aborting — Stop all load generators for a running simulation immediately to manage system resources and prevent overruns

The Gatling MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Gatling to OpenAI Agents SDK via MCP

Follow these steps to integrate the Gatling MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from Gatling

Why Use OpenAI Agents SDK with the Gatling MCP Server

OpenAI Agents SDK provides unique advantages when paired with Gatling through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Gatling + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Gatling MCP Server delivers measurable value.

Automated workflows: build agents that query Gatling, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Gatling, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Gatling tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Gatling to resolve tickets, look up records, and update statuses without human intervention

Gatling MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect Gatling to OpenAI Agents SDK via MCP:

abort_simulation

Abort a running Gatling simulation

get_run

Get full details of a Gatling run

get_simulation

Get full details of a Gatling simulation

list_packages

List uploaded packages/artifacts on Gatling Enterprise

list_pools

List load generator pools on Gatling Enterprise

list_runs

List runs for a Gatling simulation

list_simulations

Simulations define load scenarios with VU populations. Returns names, IDs, class names, and team associations. List all simulations on Gatling Enterprise

list_teams

List teams on Gatling Enterprise

list_tokens

List API tokens on Gatling Enterprise

start_simulation

Returns run ID. Start a Gatling simulation run

Example Prompts for Gatling in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Gatling immediately.

"List all simulations on Gatling Enterprise"

"Start simulation 'abc-123'"

"Show me the stats for run 'run_xyz789'"

Troubleshooting Gatling MCP Server with OpenAI Agents SDK

Common issues when connecting Gatling to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Gatling + OpenAI Agents SDK FAQ

Common questions about integrating Gatling MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.