How to Use the Chewy Ads MCP in LangChain

Q: Can I trace Chewy Ads tool execution within a LangChain run using LangSmith?

Yes, every call to getperformancereport or other tools shows up in your LangSmith dashboard automatically. You can inspect the exact latency, token usage, and raw payload returned from Chewy's API.

LangChain agents can now chain Chewy Ads operations together to automate retail media campaigns via MCP without manual scripts.

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Connect Chewy Ads MCP to LangChain

Create your Vinkius account to connect Chewy Ads to LangChain 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 Chewy Ads with LangChain

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Chain Chewy Ads campaign discovery with LangChain agents

`list_chewy_campaigns` lets your LangChain agent pull your active Chewy storefront campaigns into its execution context. It doesn't just list them; it feeds the raw campaign IDs directly into subsequent steps of your chain to analyze performance. By using this MCP Server, your LangChain agent can inspect specific campaign health by passing those IDs to `get_campaign_details`. This eliminates the need to hardcode campaign identifiers when building multi-step retail marketing chains.

Automate keyword optimization loops using LangChain

`list_adgroup_keywords` retrieves keyword bids and search metrics directly inside your LangChain agent's execution loop. Your chain can evaluate which search terms are costing you money and immediately identify underperforming targets. The LangChain agent pairs this keyword list with `list_adgroup_ads` to see which specific creatives are tied to those search terms. LangSmith tracks every step of this MCP tool retrieval, so you see exactly how your agent makes optimization decisions.

Monitor budget limits during complex agent chains

`get_chewy_account_balance` checks your remaining ad spend and budget status before your LangChain agent triggers any high-cost operations. This tool acts as a guardrail within your chain to prevent runaway spending on retail placements. You can chain this balance check with `get_performance_report` in your LangChain pipeline to calculate your actual return on ad spend in real-time. Your LangChain budget guardrail blocks spend if the Chewy ad account runs dry or if performance metrics drop below your set threshold.

Setup guide

Set up Chewy Ads MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Chewy Ads tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "chewy-ads-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Chewy Ads transactions"
    })
    print(result["messages"][-1].content)

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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 Chewy Ads. 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 Chewy Ads MCP in LangChain

Your LangChain agent handles this by passing JSON outputs from tools like `list_chewy_catalogs` directly as inputs to the next node in your graph. You don't need to write glue code to bridge your Chewy product feeds with other database tools.

Yes, every call to `get_performance_report` or other tools shows up in your LangSmith dashboard automatically. You can inspect the exact latency, token usage, and raw payload returned from Chewy's API.

Vinkius manages the authentication layer, giving you a single endpoint token to use with `MultiServerMCPClient`. Your LangChain code never has to deal with raw Chewy API keys or session refreshes.

The adapter library handles the error gracefully, returning the API error message directly to the agent. This allows your agent to catch the issue and decide whether to retry or try a different path.

Your budget metrics and campaign structures are completely safe. Vinkius runs the server in an isolated, ephemeral V8 sandbox that only processes your Chewy account balance during the active tool call. No credentials or ad spend data are ever stored on disk.

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