How to Use the Xray (Test Management) MCP in LlamaIndex
Build knowledge-augmented systems with LlamaIndex using Xray (Test Management) data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Xray (Test Management) MCP to LlamaIndex
Create your Vinkius account to connect Xray (Test Management) to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Indexing Test Results for LlamaIndex
When you run a test, the `get_execution_details` tool grabs granular results. Passing these structured outputs to LlamaIndex means those specific failure patterns or passing details become searchable knowledge. This moves beyond simple API calls; it lets your RAG application query past sessions and pull answers grounded in actual Xray data.
Retrieving Test Case Specs with MCP Server
Need to understand a specific test? The `get_test_details` tool pulls all the necessary metadata for an Xray test case. Indexing these details lets your knowledge base answer questions like, 'What is the expected outcome for TST-1?' It's perfect for training agents on organizational testing standards.
Mapping Test Plans using LlamaIndex
Use `get_test_plan_details` to pull all details about a specific test plan. Indexing this data lets your application answer complex questions, such as 'What tests are included in the Q3 regression cycle?' This ability turns structured API calls into natural language knowledge retrieval.
Set up Xray (Test Management) MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports. - 3
Convert to LlamaIndex tools
Call
mcp_tool_spec.to_tool_list_async()to convert all Xray (Test Management) MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
# Connect to the MCP
mcp_client = BasicMCPClient(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)
# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()
# Create and run the agent
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt="You have access to Xray (Test Management) tools.",
)
response = await agent.run("List recent Xray (Test Management) data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Xray (Test Management). 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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Common questions about Xray (Test Management) MCP in LlamaIndex
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