Xray (Test Management) MCP Server for Pydantic AI 9 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Xray (Test Management) through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Xray (Test Management) "
"(9 tools)."
),
)
result = await agent.run(
"What tools are available in Xray (Test Management)?"
)
print(result.data)
asyncio.run(main())
* 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 Xray (Test Management) MCP Server
Connect your Xray Test Management account to any AI agent and manage your quality assurance workflows through natural conversation.
Pydantic AI validates every Xray (Test Management) tool response against typed schemas, catching data inconsistencies at build time. Connect 9 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Test Case Discovery — List and browse all test cases within your project and retrieve unique test keys (e.g., TST-1) for deep inspection
- Execution Monitoring — List and track test execution records to monitor real-time QA results and overall release readiness
- Granular Results — Retrieve detailed results for specific executions to see which steps passed, failed, or encountered errors
- Test Planning — Browse high-level test plans and retrieve scope details to understand your testing strategy and progress
- Logical Grouping — List test sets to see how individual test cases are organized into functional or regression groups
- Historical Auditing — Retrieve the complete run history for a single test across multiple execution cycles to identify flaky tests
- Project Config — Verify environment settings and status mappings to ensure your agent is aligned with your project's workflow
The Xray (Test Management) MCP Server exposes 9 tools through the Vinkius. Connect it to Pydantic AI 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 Xray (Test Management) to Pydantic AI via MCP
Follow these steps to integrate the Xray (Test Management) MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 9 tools from Xray (Test Management) with type-safe schemas
Why Use Pydantic AI with the Xray (Test Management) MCP Server
Pydantic AI provides unique advantages when paired with Xray (Test Management) through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Xray (Test Management) integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Xray (Test Management) connection logic from agent behavior for testable, maintainable code
Xray (Test Management) + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Xray (Test Management) MCP Server delivers measurable value.
Type-safe data pipelines: query Xray (Test Management) with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Xray (Test Management) tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Xray (Test Management) and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Xray (Test Management) responses and write comprehensive agent tests
Xray (Test Management) MCP Tools for Pydantic AI (9)
These 9 tools become available when you connect Xray (Test Management) to Pydantic AI via MCP:
get_execution_details
Retrieves granular results for a specific test execution
get_individual_test_runs
Retrieves individual test run instances for a specific test
get_test_details
Retrieves comprehensive details for a specific Xray test case
get_test_plan_details
Retrieves details for a specific test plan
get_xray_settings
Retrieves Xray project configuration and field mappings
list_test_executions
Lists all test execution records
list_test_plans
Lists all test plans configured in Xray
list_test_sets
Lists all test sets (groups of tests)
list_xray_tests
g. TST-1). Lists all test cases in the Xray project
Example Prompts for Xray (Test Management) in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Xray (Test Management) immediately.
"List all test cases in the 'Mobile-App' project."
"What were the results for execution 'EXEC-555'?"
"Show me the test plan progress for 'v2.4 Release'."
Troubleshooting Xray (Test Management) MCP Server with Pydantic AI
Common issues when connecting Xray (Test Management) to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiXray (Test Management) + Pydantic AI FAQ
Common questions about integrating Xray (Test Management) MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Xray (Test Management) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Xray (Test Management) to Pydantic AI
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.