VTEX Catalog MCP Server for CrewAI 7 tools — connect in under 2 minutes
Connect your CrewAI agents to VTEX Catalog through the Vinkius — pass the Edge URL in the `mcps` parameter and every VTEX Catalog tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="VTEX Catalog Specialist",
goal="Help users interact with VTEX Catalog effectively",
backstory=(
"You are an expert at leveraging VTEX Catalog tools "
"for automation and data analysis."
),
# Your Vinkius token — get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in VTEX Catalog "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 7 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About VTEX Catalog MCP Server
Connect your VTEX Catalog API to any AI agent and manage your entire product catalog through natural conversation.
When paired with CrewAI, VTEX Catalog becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call VTEX Catalog tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.
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 CrewAI 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 CrewAI via MCP
Follow these steps to integrate the VTEX Catalog MCP Server with CrewAI.
Install CrewAI
Run pip install crewai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Customize the agent
Adjust the role, goal, and backstory to fit your use case
Run the crew
Run python crew.py — CrewAI auto-discovers 7 tools from VTEX Catalog
Why Use CrewAI with the VTEX Catalog MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with VTEX Catalog through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
VTEX Catalog + CrewAI Use Cases
Practical scenarios where CrewAI combined with the VTEX Catalog MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries VTEX Catalog for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries VTEX Catalog, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain VTEX Catalog tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries VTEX Catalog against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
VTEX Catalog MCP Tools for CrewAI (7)
These 7 tools become available when you connect VTEX Catalog to CrewAI 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 CrewAI
Ready-to-use prompts you can give your CrewAI 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 CrewAI
Common issues when connecting VTEX Catalog to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
VTEX Catalog + CrewAI FAQ
Common questions about integrating VTEX Catalog MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect VTEX Catalog with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect VTEX Catalog to CrewAI
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.
