How to Use the Mercado Livre Catalog MCP in Google ADK

Q: How do I limit which tools the Google ADK sees in the Mercado Livre Catalog?

You use the toolnames filter during initialization. By passing an array of allowed strings, you ensure the agent only has access to the tools you explicitly permit, like getitem or updateprice.

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Connect Mercado Livre Catalog MCP to Google ADK

Create your Vinkius account to connect Mercado Livre Catalog to Google ADK 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 Mercado Livre Catalog with Google ADK

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Direct catalog interaction via Google ADK

Connect your Gemini-powered agents to the catalog using the McpToolset. This allows your agent to trigger `search_items` based on data currently residing in your BigQuery tables. The integration handles the transport layer for you. You just define the agent, pass the toolset, and let the model decide when to query or update your listings.

Granular inventory adjustments

Managing stock levels across high-volume accounts requires precision. Use `update_stock` to push changes from your internal Google Cloud infrastructure directly to the marketplace. Because the Google ADK supports tool filtering, you can restrict your agent to only use specific tools for safety. This limits the blast radius of any automated logic.

Dynamic attribute validation

Marketplace requirements change often. Your agent calls `get_domain_attributes` to verify the schema before attempting an `update_item` request. This prevents the agent from sending malformed data to the platform. It keeps your listings compliant without requiring code changes whenever the marketplace updates its rules.

Setup guide

Set up Mercado Livre Catalog MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Mercado Livre Catalog tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Mercado Livre Catalog_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mercado Livre Catalog tools via MCP.",
    tools=mcp_tools,
)

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

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Common questions about Mercado Livre Catalog MCP in Google ADK

It supports both Stdio and HTTP transports. For most production deployments in Google Cloud, you will use the HTTP transport to point at your hosted MCP Server endpoint.

You use the tool_names filter during initialization. By passing an array of allowed strings, you ensure the agent only has access to the tools you explicitly permit, like `get_item` or `update_price`.

Yes. Gemini models with high token windows can reason over large catalog dumps. By using the toolset, your agent can process many items in a single reasoning session.

The server reports errors when you hit rate limits. Your agent logic should include retry patterns or backoff strategies to handle these platform-side restrictions gracefully.

The MCP Server acts as an isolated gatekeeper. It only processes the specific listing identifiers and price values you send it. Your raw account credentials remain protected by the Vinkius-managed endpoint token.

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