How do I get my VTEX API credentials?

Log in to your VTEX Admin, go to **Account Settings → Application Keys**, and create a new App Key. You'll receive an App Key and App Token pair. You also need your Account Name (the subdomain you use to access the VTEX Admin, e.g., 'mystore'). Ensure the key has **Catalog** and **Logistics** read/write permissions. No code, no SDK — just connect and go.

Can my agent update stock levels without opening the VTEX Admin?

Yes! Use the 'manage_stock' tool with a SKU ID and the new quantity. Your agent updates the inventory balance in real-time through the VTEX Logistics API — perfect for warehouse teams receiving shipments who need to update stock counts without navigating to the Inventory module.

How does product search work with categories and brands?

The 'search_products' tool supports three search modes: full-text (e.g., 'Nike Running Shoes'), by brand ID (e.g., 'b/1234'), or by category ID (e.g., 'c/5678'). This means your agent can quickly audit all products under a specific brand or explore an entire product category — no manual catalog browsing required.

Can I create new products and manage my entire catalog via AI?

Absolutely. The 'save_product' tool lets your agent create or update products by sending a structured JSON body. Combined with 'get_category' and 'get_brand' for classification, your agent can handle the full product lifecycle — from initial creation to SKU-level stock adjustments — ideal for merchandising teams managing large VTEX catalogs with thousands of products.

VTEX Catalog MCP Server for LlamaIndex 7 tools — connect in under 2 minutes

Name: VTEX Catalog
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 7 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add VTEX Catalog as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to VTEX Catalog. "
            "You have 7 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in VTEX Catalog?"
    )
    print(response)

asyncio.run(main())

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About VTEX Catalog MCP Server

Connect your VTEX Catalog API to any AI agent and manage your entire product catalog through natural conversation.

LlamaIndex agents combine VTEX Catalog tool responses with indexed documents for comprehensive, grounded answers. Connect 7 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Product Search — Run full-text searches across your product catalog by name, brand ID, or category ID. Returns complete product listings with pricing, availability, and images.
Product Details — Retrieve the full specification sheet of any product by ID, including all associated SKUs, categories, dimensions, and metadata.
Product Management — Create or update products directly from your agent. Send structured product data and have it reflected in your VTEX catalog immediately.
SKU Inspection — Look up specific SKUs with detailed attributes like price, weight, dimensions, EAN, and stock status.
Stock Management — Update the available quantity of any SKU across your logistics warehouses. Adjust inventory in real-time without opening the VTEX Admin.
Category & Brand Lookup — Explore your category tree and brand directory to understand how your catalog is organized and ensure correct product classification.

The VTEX Catalog MCP Server exposes 7 tools through the Vinkius. Connect it to LlamaIndex 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 VTEX Catalog to LlamaIndex via MCP

Follow these steps to integrate the VTEX Catalog MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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 7 tools from VTEX Catalog

Why Use LlamaIndex with the VTEX Catalog MCP Server

LlamaIndex provides unique advantages when paired with VTEX Catalog through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine VTEX Catalog tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain VTEX Catalog tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query VTEX Catalog, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what VTEX Catalog tools were called, what data was returned, and how it influenced the final answer

VTEX Catalog + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the VTEX Catalog MCP Server delivers measurable value.

Hybrid search: combine VTEX Catalog real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query VTEX Catalog to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying VTEX Catalog for fresh data

Analytical workflows: chain VTEX Catalog queries with LlamaIndex's data connectors to build multi-source analytical reports

VTEX Catalog MCP Tools for LlamaIndex (7)

These 7 tools become available when you connect VTEX Catalog to LlamaIndex via MCP:

get_brand

Get details of a brand

get_category

Get details of a category

get_product

Get full details of a specific product

get_sku

Get details of a specific SKU

manage_stock

Update the available quantity of a SKU

save_product

Create or update a product

search_products

Examples: "Coca Cola", "b/1234" (brand ID), "c/5678" (category ID). Search for products by text, brand, or category

Example Prompts for VTEX Catalog in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with VTEX Catalog immediately.

"Search for 'Nike Air Max' in my VTEX catalog"

"Update the stock of SKU 12345 to 150 units"

"Show me the details of category 5678"

Troubleshooting VTEX Catalog MCP Server with LlamaIndex

Common issues when connecting VTEX Catalog to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

VTEX Catalog + LlamaIndex FAQ

Common questions about integrating VTEX Catalog MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query VTEX Catalog tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.