How to Use the PractiTest MCP in LlamaIndex

Q: Can LlamaIndex query specific PractiTest runs?

Yes. The agent invokes the gettest or listruns tools, turning the raw JSON responses into searchable nodes within your index.

Q: How do I restrict which projects the agent sees?

Use the allowedtools filter during setup. You can also hardcode specific project IDs into the prompt so the agent only runs listinstances on approved workspaces when using the MCP integration.

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Setup PractiTest with LlamaIndex

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Index requirements and tests

Stop guessing what coverage you already have. By wrapping this MCP server in a McpToolSpec, your LlamaIndex application can call `list_requirements` and `list_tests` to pull your entire QA hierarchy. The framework then embeds these records into a semantic index. When a developer asks about login validation, the agent queries the vector store instead of hallucinating a response.

Deep historical analysis with LlamaIndex

You can build RAG pipelines that understand past failures. The agent uses `list_runs` to grab recent execution history, then calls `get_test` to pull the exact steps that failed. Combining live API data with your internal documentation creates a highly accurate knowledge base. The system knows exactly why a specific instance failed last Tuesday because it read the actual run logs.

Grounded test generation via the MCP Server

Reading data is only half the job. Once your application identifies a missing scenario through semantic search, it triggers `create_test` to fill the gap. You configure the FunctionAgent to format the JSON payload based on similar, previously indexed tests. This ensures new records match your team's existing writing style and structural conventions.

Setup guide

Set up PractiTest 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 PractiTest 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 PractiTest tools.",
)
response = await agent.run("List recent PractiTest data")

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Common questions about PractiTest MCP in LlamaIndex

Install llama-index-tools-mcp and instantiate a BasicMCPClient. Then pass the client to McpToolSpec and convert it using to_tool_list_async().

Yes. The agent invokes the `get_test` or `list_runs` tools, turning the raw JSON responses into searchable nodes within your index.

No. The tools fetch live data during the execution loop. If a requirement updates, the next `get_requirement` call pulls the fresh version directly.

Use the allowed_tools filter during setup. You can also hardcode specific project IDs into the prompt so the agent only runs `list_instances` on approved workspaces when using the MCP integration.

Yes. The server only transmits test definitions, project IDs, and run statuses. Vinkius enforces zero-trust boundaries, meaning your LlamaIndex embeddings stay completely private within your own infrastructure.

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