Bring Test Management
to CrewAI
Create your Vinkius account to connect Qase to CrewAI and start using all 10 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Qase MCP Server?
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
- Subscribe to this server
- Authorize via your Qase API Token
- 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
Built-in capabilities (10)
Retrieves details for a specific test case
Retrieves details for a specific project
Retrieves details for a specific test run
Lists test cases in a project
Lists all defects linked to test case failures
Lists all milestones in a project
Lists all test plans in a project
Lists all projects in Qase
Lists all test runs in a project
Lists test suites in a project
Why CrewAI?
When paired with CrewAI, Qase becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Qase tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Qase in CrewAI
Why run Qase with Vinkius?
The Qase connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 10 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Qase using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Qase and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Qase to CrewAI through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Qase for CrewAI
Every request between CrewAI and Qase is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
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.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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