How to Use the Mabl (AI-Powered Test Automation) MCP in LlamaIndex

Turn your LlamaIndex knowledge base into a living record of Mabl (AI-Powered Test Automation) results and test history.

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Connect Mabl (AI-Powered Test Automation) MCP to LlamaIndex

Create your Vinkius account to connect Mabl (AI-Powered Test Automation) 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.

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Setup Mabl (AI-Powered Test Automation) with LlamaIndex

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Index test executions for semantic search

Feed output from `mb.list_executions` directly into your vector store to make your test history queryable. You can ask your agent to find patterns in past failures across specific application versions. This turns raw API responses into a searchable knowledge base. Your agent retrieves historical context to explain why a test plan might be struggling.

Map test plans to your documentation

Use `mb.list_plans` to pull your current testing roadmap into your index. This allows your agent to link user stories with the actual test plans that verify them. By indexing plan names and statuses, your agent provides accurate answers about coverage. It understands which features are currently tested without needing manual documentation updates.

Verify environment configurations

Query `mb.list_envs` to keep your knowledge base updated on current staging and production targets. Your agent maintains a live view of where your code is running. This ensures your RAG application has the latest context. When you ask about environment health, the agent uses the most current data from your Mabl workspace.

Setup guide

Set up Mabl (AI-Powered Test Automation) MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
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 provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to 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 Mabl (AI-Powered Test Automation) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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 Mabl (AI-Powered Test Automation) tools.",
)
response = await agent.run("List recent Mabl (AI-Powered Test Automation) data")

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Common questions about Mabl (AI-Powered Test Automation) MCP in LlamaIndex

Use the MCP tool spec to fetch data and ingest it into your index. This allows your agent to reference live test results during the retrieval process.

Yes. By indexing the output of the listing tools, you enable your agent to answer questions about past test performance and failure trends.

It provides grounded data about your software quality. Your agent stops hallucinating about build health and reports based on actual execution logs.

The client communicates with the server via an authenticated endpoint. It fetches the required data, which is then processed by your ingestion pipeline.

Your workspace credentials are encrypted and scoped to the server instance. No sensitive configuration data is ever stored in the vector index itself.

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