How to Use the PrestaShop MCP in LlamaIndex

Q: How do I convert PrestaShop tools into LlamaIndex tool specs?

Install llama-index-tools-mcp and initialize the MCP client with your Vinkius URL. You then call McpToolSpec to wrap the tools, making listproducts and getorder instantly accessible to your LlamaIndex agents.

Q: Can LlamaIndex index PrestaShop customer lists for CRM search?

Yes, you can use listcustomers to pull CRM records and index them into a local vector store. This allows your LlamaIndex agent to search for customer accounts using semantic queries instead of exact database matches.

Q: How do I prevent LlamaIndex from hallucinating PrestaShop stock counts?

You configure your agent to call getstock directly before answering any inventory questions. This ensures the agent uses the live API response rather than relying solely on older cached vector embeddings.

Index PrestaShop products and orders into LlamaIndex vector stores for semantic search without hallucinations.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect PrestaShop MCP to LlamaIndex

Create your Vinkius account to connect PrestaShop to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup PrestaShop with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Index PrestaShop catalogs into LlamaIndex RAG pipelines

The `list_products` tool fetches your entire store catalog so you can convert raw product descriptions into searchable vector embeddings. LlamaIndex uses these embeddings to answer customer queries with actual store data instead of making up details. It stops hallucinations cold. This MCP Server feeds parsed XML nodes directly into your indexing pipeline. When a user asks about a product, your agent runs a semantic search over the indexed data and uses `get_product` to fetch live prices. It keeps your search results grounded.

Run semantic search over PrestaShop order histories

The `list_orders` tool retrieves your recent sales history to build a searchable index of customer transactions. Your LlamaIndex agent can query this index to find patterns in orders without scanning the database manually. It saves hours of manual work. Connecting this MCP Server to your historical indices lets you drill down on a specific transaction. The agent uses `get_order` to pull line items and payment success paths. This connects live API data with your historical indices in a single query interface.

Track stock levels with LlamaIndex query engines

The `list_stock` tool outputs actual physical inventory units that your LlamaIndex query engine can parse. This gives your agent a real-time snapshot of what is actually on your warehouse shelves. It cuts down on overselling. By calling `get_stock` during a query run, the agent verifies that the indexed product data matches the actual quantity available. This keeps your RAG applications grounded in real-time inventory realities. No stale data.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by PrestaShop. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect PrestaShop now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about PrestaShop MCP in LlamaIndex

Install `llama-index-tools-mcp` and initialize the MCP client with your Vinkius URL. You then call `McpToolSpec` to wrap the tools, making `list_products` and `get_order` instantly accessible to your LlamaIndex agents.

Yes, you can use `list_customers` to pull CRM records and index them into a local vector store. This allows your LlamaIndex agent to search for customer accounts using semantic queries instead of exact database matches.

You configure your agent to call `get_stock` directly before answering any inventory questions. This ensures the agent uses the live API response rather than relying solely on older cached vector embeddings.

Yes, you can restrict the agent's access by passing an allowed tools list to this MCP Server. For example, you can limit a customer-facing agent to `list_products` and `get_product` while blocking access to order or customer lists.

Your PrestaShop catalog, customer profiles, and address details stay inside your designated LlamaIndex vector store. Vinkius operates as a stateless proxy inside a secure V8 sandbox, meaning no store data is cached or saved on Vinkius infrastructure.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript