Can I use my regular TestRail password to authenticate?

Technically yes, as TestRail uses HTTP Basic Auth. However, it is highly discouraged for security purposes. The gold standard is to generate a dedicated API Key via your profile interface strictly tied to this connection.

Why isn't the API agent responding despite my credentials being correct?

TestRail requires the instance administrator to explicitly configure system-level API enablement. Ask your workspace admin to go to Administration > Site Settings > API and tick 'Enable API' box.

Can the AI rewrite my test cases explicitly inside your TestRail app?

No. Consistent with security best practices, the TestRail MCP functions only as a powerful read-only query extraction engine. It retrieves metadata, sections, milestones, and reports, protecting your ground-truth data from accidental AI deletion.

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

Name: TestRail
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 TestRail through the 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="TestRail Assistant",
            instructions=(
                "You help users interact with TestRail. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from TestRail"
        )
        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 TestRail MCP Server

Bring your overarching TestRail quality assurance orchestration directly to your developer's edge. Query comprehensive test coverage, inspect failing builds, and extract explicit test steps using natural conversation.

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

What you can do

Project Triage — Extract active test projects, their numeric IDs, and overall suite architecture logic
Suite & Case Isolation — Retrieve precise step-by-step logic, preconditions, and validation targets for any manual test case stored by QA
Run Execution Metrics — Instantly generate summaries around active 'Test Runs', seeing precisely which specific tests passed or failed
Milestone Navigation — Interrogate upcoming QA deadlines and release milestones without ever touching the heavy web browser application
Deep Hierarchical Search — Pull Section lists (folder hierarchies) from within projects to navigate robust test repositories visually in markdown

The TestRail 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 TestRail to OpenAI Agents SDK via MCP

Follow these steps to integrate the TestRail 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 TestRail

Why Use OpenAI Agents SDK with the TestRail MCP Server

OpenAI Agents SDK provides unique advantages when paired with TestRail 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

TestRail + OpenAI Agents SDK Use Cases

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

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

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

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

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

TestRail MCP Tools for OpenAI Agents SDK (10)

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

get_test_case_details

Retrieves full details for a specific test case

get_test_project_details

Retrieves details for a specific TestRail project

get_test_run_details

Retrieves details for a specific test run

list_project_milestones

Lists all milestones within a project

list_project_sections

Lists all sections (folders) within a project

list_run_tests

Lists all tests (case instances) within a specific test run

list_test_cases

Lists all test cases in a project, optionally filtered by suite

list_test_projects

Project IDs are essential for navigating most other resources. Lists all test projects available on the TestRail instance

list_test_runs

Lists all test runs within a specific project

list_test_suites

Lists all test suites within a specific project

Example Prompts for TestRail in OpenAI Agents SDK

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

"What active TestRail projects are available in this instance?"

"Get the manual preconditions and test steps for Test Case 1285."

"Return exact status summary for Test Run ID 403."

Troubleshooting TestRail MCP Server with OpenAI Agents SDK

Common issues when connecting TestRail 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.

TestRail + OpenAI Agents SDK FAQ

Common questions about integrating TestRail 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.