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Qase MCP Server

Name: Qase
Availability: InStock
Author: Vinkius

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Bring Qase test management into your AI workflow — list projects, track test runs, inspect cases, and monitor defects directly from your chat.

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What is the Qase MCP Server?

The Qase MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Qase via 10 tools. Bring Qase test management into your AI workflow — list projects, track test runs, inspect cases, and monitor defects directly from your chat. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.

Built-in capabilities (10)

get_caseget_projectget_runlist_caseslist_defectslist_milestoneslist_planslist_projectslist_runslist_suites

Tools for your AI Agents to operate Qase

Ask your AI agent "List all Qase projects and show me their overall health." and get the answer without opening a single dashboard. With 10 tools connected to real Qase data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.

Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.

Why teams choose Vinkius

One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.

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Qase MCP Server capabilities

10 tools

get_case

Retrieves details for a specific test case

get_project

Retrieves details for a specific project

get_run

Retrieves details for a specific test run

list_cases

Lists test cases in a project

list_defects

Lists all defects linked to test case failures

list_milestones

Lists all milestones in a project

list_plans

Lists all test plans in a project

list_projects

Lists all projects in Qase

list_runs

Lists all test runs in a project

list_suites

Lists test suites in a project

What the Qase MCP Server unlocks

Connect your Qase workspace to any AI agent and integrate test management deeply into your development workflow.

What you can do

Project Overviews — Retrieve all active projects, view health metrics, and get total counts of test cases, runs, and defects instantly
Test Cases & Suites — Explore your test hierarchy, pull specific test steps, and check case automation statuses without opening the Qase dashboard
Test Runs & Execution — List all test runs, monitor execution status (passed, failed, blocked), and dive deep into test run analytics
Defects & Milestones — Track project milestones and extract all logged defects linked to failed test cases, complete with severity levels and issue links

How it works

1. Subscribe to this server
2. Authorize via your Qase API Token
3. Start managing QA operations directly from Claude, Cursor, or any MCP-compatible client

Who is this for?

QA Engineers — quickly pull up test case steps while writing automated scripts in your IDE
Developers — ask your agent to list recent defects or failed runs related to the feature you just deployed
Product Managers — get instant summaries of test run coverage and milestone completion metrics

Frequently asked questions about the Qase MCP Server

How do I securely obtain my Qase Token?

Log in to Qase.io and click your profile icon to go to Account settings. Select API Tokens (or sometimes found under Apps for an integration token), and click Create a new API token. Add a name, click generate, and copy the string provided. It takes exactly 15 seconds. Paste it here to authenticate. Your token is encrypted at rest and injected securely at runtime.

Can my AI write test scripts using the case details?

Absolutely. Inside your IDE (like Cursor), you can ask the agent to 'Fetch case #12 from Qase project PROJ'. The tool retrieves the precise steps, preconditions, and expected results. The agent can then automatically generate Playwright, Cypress, or Selenium scripts based exactly on those Qase definitions.

How can I check the results of a recent QA cycle?

Ask your agent to list_runs for your project. This will surface your recent executions. If you notice a run with a high failure rate, ask the agent to pull get_run with that run's ID to dive into specifics and see which modules failed the automated checks.

Can it help me track Jira bugs linked to tests?

Yes. By using the list_defects capability, your AI can pull all registered defects in a Qase project. If your Qase is integrated with Jira or GitHub, the returned defect data includes external issue links, helping developers immediately map a failed test to the corresponding engineering ticket.