Zephyr Scale MCP. Audit, track, and report on QA cycles through chat.
Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Zephyr Scale (SmartBear) connects your AI client directly to your Jira-managed test suite. It lets you manage test cases, cycles, and executions using natural conversation.
Instead of navigating complex plugins, you can ask for specific keys (like PROJ-T1), check the progress of a regression cycle, or audit environments—all through chat.
What your AI agents can do
Get execution
Retrieves full details and step-by-step results for a specific Zephyr Scale test run.
Get test case
Pulls all objective data, preconditions, and detailed scripts for one specific test case.
Get test cycle
Retrieves full details about a grouped set of test runs associated with a release or sprint.
The agent pulls all objective text, preconditions, and detailed scripts for any individual test case using get_test_case.
You get step-by-step results (Pass/Fail/Blocked) and time taken for a specific run by calling get_execution.
The system pulls grouped test runs for a release or sprint, giving you the current progress percentage via get_test_cycle.
List all available environments (Staging/Prod) and custom statuses in your project using list_environments and list_statuses.
Find test cases, cycles, or plans by traversing the organizational folder hierarchy with list_folders.
Ask AI about this MCP
Supported MCP Clients
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Zephyr Scale (SmartBear): 10 Tools for QA Testing
These tools let your agent perform specific actions—from listing environments to getting step-by-step failure details—giving you full control over test data through conversation.
019d7628get execution
Retrieves full details and step-by-step results for a specific Zephyr Scale test run.
019d7628get test case
Pulls all objective data, preconditions, and detailed scripts for one specific test case.
019d7628get test cycle
Retrieves full details about a grouped set of test runs associated with a release or sprint.
019d7628list environments
Lists all configured testing environments (like Staging or Production) in your Zephyr Scale project.
019d7628list executions
Shows a list of all test runs that have occurred in the Zephyr Scale project.
019d7628list folders
Lists organizational folders, restricted to Test Case, Cycle, or Plan types within a project.
019d7628list statuses
Retrieves all custom status names used for test execution results in your current project.
019d7628list test cases
Lists available test cases within a specific Jira project, showing their keys and statuses.
019d7628list test cycles
Retrieves a list of all grouped test cycles for the entire Zephyr Scale project.
019d7628list test plans
Lists all high-level test plans that define overall testing strategy in your project.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Make Your AI Do More
Start with Zephyr Scale (SmartBear), then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
Listen up. Forget clicking through a dozen Jira plugins just to see if your tests passed. This server hooks up your agent directly to your Zephyr Scale project so you don't gotta navigate any complex menus; you just talk to it. It handles all the heavy lifting, giving you the full picture without making you feel like an IT intern.
To find what you need: You can ask your AI client to pull up a list of all high-level test plans that define your whole testing strategy using list_test_plans. Need to see how things are organized? Use list_folders to browse the entire organizational hierarchy, whether it's for Test Cases, Cycles, or Plans.
For actual tests, you can get a quick rundown of all available test cases in a specific Jira project via list_test_cases, and if you need every single detail—the objective text, preconditions, and full scripts—you just call up get_test_case for any individual script.
To track down your work: You can pull a list of all grouped test cycles using list_test_cycles, which lets you see the major milestones. If you're checking on a specific sprint or release, calling get_test_cycle pulls up those full details and tells you exactly where things stand. For a complete audit trail, use list_executions to get a list of every single test run that’s ever happened in the project.
To check progress: When you need deep status checks, calling get_execution gives you the whole nine yards: step-by-step results and how long it took for one specific test run. If you're trying to scope out what environments are live, list_environments shows you every configured place—like Staging or Production—where your code runs.
You can also check all the custom status names used for results with list_statuses.
The full picture: When you combine these calls, you're covered. You use list_folders to browse assets, get_test_case to understand a single test, and then use get_execution or get_test_cycle to see how that test performed in the wild. If you need to know which tests exist at all, list_test_cases gives you their keys and current status.
You'll find everything from browsing the whole project structure with list_folders to checking the full scope of grouped runs using list_test_cycles. It’s basically your entire QA operations manual, but instead of reading it, you just ask your agent.
How Zephyr Scale MCP Works
- 1 First, subscribe to this server and provide your Zephyr Scale API Token.
- 2 Next, tell your AI agent what data you need—for example, 'Show me the status of the regression cycle for Q1.'
- 3 The agent executes the necessary tools (like
get_test_cycle) against your Jira instance and delivers a formatted summary.
The bottom line is that your AI client talks directly to Zephyr Scale, so you don't have to navigate complex dashboards yourself.
Who Is Zephyr Scale MCP For?
This is for the QA Engineer who spends too much time clicking tabs just to verify a test step. It’s for the Test Manager who needs quick oversight of cycle progress without running manual filters. If you're tired of guessing where a specific test script lives, this server helps.
Checks get_test_case for detailed scripts or runs get_execution to pinpoint exactly which step failed during a recent run.
Uses list_test_cycles and list_test_plans to verify overall test coverage before a major release milestone.
Checks the execution status of all regression cycles by calling get_test_cycle right before giving the go-ahead for production deployment.
What Changes When You Connect
- Get granular failure data immediately. Instead of clicking into a massive execution ID just to find out why it failed, use
get_executionto pull step-by-step progress details in one go. - See project scope at a glance. Use
list_environmentsto quickly check if the test run results are from Staging or Production without manually checking Jira ticket metadata. - Understand what's being tested. Run
get_test_casefor any key (e.g., PROJ-T1) and instantly get the full objective, preconditions, and script details—no more clicking through multiple tabs. - Manage scope creep visibility. Use
list_test_plansto see the high-level strategy of testing across the whole project, verifying that all necessary areas are covered before a release. - Track group progress instantly. Instead of filtering by sprint date or release name, use
list_test_cyclesandget_test_cycleto get an immediate summary of current completion rates.
Real-World Use Cases
Debugging a Failed Feature
A QA Engineer finds a failure in the login module. Instead of manually jumping into Jira and searching by run ID, they ask their agent: 'Show me the steps for PROJ-T12 and the results from execution 9876.' The agent runs get_test_case then get_execution, giving them the failed step details instantly so they can debug with the developer.
Pre-Release Audit
A Release Manager needs to know if all major features were tested before deployment. They prompt: 'List all test cycles that include the 'Payment' area.' The agent runs list_test_cycles and then summarizes progress from get_test_cycle, ensuring sign-off criteria are met.
Assessing Project Scope
A new Test Manager joins the team and needs to understand the entire testing structure. They ask: 'What test plans exist, and what folders organize them?' The agent uses list_test_plans and then calls list_folders, mapping out the whole project's QA architecture.
Checking Environment Parity
A developer needs to confirm if all teams are testing against the correct environment. They ask: 'What environments can we run tests on?' The agent uses list_environments, confirming available targets like Staging and Production, preventing deployment errors.
The Tradeoffs
Manual Jira Navigation
Spending 15 minutes clicking from the main dashboard to the Test Plan tab, then filtering by Sprint, then opening a specific Cycle, and finally looking up an Execution ID.
→
Just ask your agent: 'Check the progress of the Regression Q2 cycle.' The agent handles list_test_cycles and get_test_cycle in one command, giving you the status immediately.
Guessing Test Keys
Knowing a test exists but forgetting its exact key (e.g., PROJ-T12). You waste time searching through hundreds of results.
→
First, run list_test_cases to get the keys and names for your project. Then, pass that specific key to get_test_case for guaranteed retrieval.
Ignoring Test Structure
Thinking all test cases are in one pool, making it impossible to scope down testing efforts by functional area.
→
Use list_folders to map the project's hierarchy. This lets you focus your queries on a specific folder type (TEST_CYCLE or TEST_CASE) without wading through unrelated data.
When It Fits, When It Doesn't
Use this server if your pain point is retrieving deep, structured testing metadata from Jira/Zephyr Scale. Specifically: If you need to know why a test failed, use get_execution. If you need the full script for a test, run get_test_case. If you only care about overall progress relative to a release date, stick with list_test_cycles and get_test_cycle.
Don't use this if your primary goal is running tests (that's the job of Zephyr Scale itself). Also, don't try to process raw log files; for that, you need a dedicated logging tool. This server works best when you need information about the test run—the status, the steps, or the scope.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zephyr Scale (SmartBear). All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Finding test scripts and cycle progress shouldn't take half an hour of clicking.
Today, if a QA Engineer needs to check the details for a specific test case—say, 'User Login'—they have to navigate Jira. They find the Test Plan, then click into the associated Cycle, and finally drill down to the individual Case record just to copy the objective text or preconditions. It’s four clicks and three tabs deep.
With this MCP server, you just tell your agent: 'Get me all details for PROJ-T1.' The agent runs `get_test_case`, pulls every field—objectives, steps, prerequisites—and hands it back to you in plain text. You get the data instantly.
Zephyr Scale MCP Server: Get cycle status and execution results.
Manually checking a regression run means jumping between `list_test_cycles` to see what's running, then clicking into the specific Cycle ID, and finally trying to interpret the aggregated results from multiple executions. The progress bar is only as good as the last person who updated it.
The agent streamlines this. By calling `get_test_cycle`, you get a single, comprehensive status update for that entire group of tests. You don't just see 'In Progress'; you see *how* much is done and how many executions are involved.
Common Questions About Zephyr Scale MCP
How does the get_test_case tool work? +
The get_test_case tool retrieves all underlying details for a single test case using its unique key. It gives you the objective, preconditions, and detailed script steps for deep inspection.
Can I list environments with list_environments? +
Yes, list_environments pulls every configured environment (like Staging or Production) available in your project. This is critical for knowing which data set you're looking at.
What is the difference between list_test_cases and list_executions? +
These tools serve different purposes: list_test_cases shows you what tests exist in your project. list_executions shows you a history of when those tests were run.
Do I need list_test_plans to use get_test_cycle? +
No, they are separate views. You use get_test_cycle when you need the current status of a defined group run. You use list_test_plans when you want to see the overarching strategy that contains those cycles.
How do I check test progress for an entire sprint? +
You call get_test_cycle, passing in the specific cycle ID associated with that sprint. This returns the overall status and a breakdown of how many steps have passed versus failed.
How do I set up authentication for the list_test_cases tool? +
You must provide a valid Zephyr Scale API Token. This token authenticates your connection to the server, giving your agent permission to read and process test case data from your specific Jira project.
When using list_executions, can I filter results by status like 'Failed' or 'Passed'? +
Yes, you can specify a desired status. You pass filters (e.g., failed/passed) to the server, allowing your agent to retrieve only test runs that meet specific quality criteria.
What is the purpose of list_folders and how does it work? +
It maps out the project's organizational structure. You specify a folder type (like TEST_CASE or TEST_PLAN) to see where those items are nested within the overall Zephyr Scale hierarchy.
Can I check the specific test steps for a case through the agent? +
Yes. The get_test_case tool allows your AI agent to retrieve the full script for any test key, providing the exact sequence of steps, test data, and expected results defined in Zephyr Scale.
How do I see the progress of a specific test cycle via chat? +
Use the get_test_cycle tool. Provide the unique cycle key, and your agent will return the cycle status, planned dates, and high-level execution statistics to help you monitor testing progress.
Is it possible to see the results of individual test runs? +
Absolutely. Using the get_execution_details tool, your agent can retrieve step-by-step results for any execution, including comments and execution time, helping you identify exactly where a test failed.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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