How to Use the Walmart Connect Ads MCP in LlamaIndex

Q: How do I use Walmart Connect Ads and LlamaIndex together?

You run tools like adsgetitemhealthreport to generate data, then you index that output. Later, you query the knowledge base using natural language against the indexed ad performance metrics.

Q: Can LlamaIndex help me track changes using Walmart Connect Ads?

Yes. You can index the output from adsgetcpcmetrics every few hours. This builds a time-series knowledge graph that you can query against to spot unusual spending patterns or sudden drops in impressions.

Q: What is the optimal way to get keyword data using Walmart Connect Ads and LlamaIndex?

You run adsgetkeywordperformance, index the resulting table, and then ask specific questions against that indexed knowledge. For example: 'Show me all keywords with a bid over $2.00 that performed poorly last week.'

Index and search ad data with LlamaIndex using the Walmart Connect Ads MCP Server.

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Connect Walmart Connect Ads MCP to LlamaIndex

Create your Vinkius account to connect Walmart Connect Ads to LlamaIndex 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 Walmart Connect Ads with LlamaIndex

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Building Knowledge from Ad Metrics via LlamaIndex

Don't just run reports; save them. Your AI client uses `ads_get_item_health_report` to generate a performance snapshot, then indexes that entire report into your vector store. You can later query the index and ask, 'Why did my item health drop last quarter?' and get an answer grounded in the actual API data. This turns transient ad reports into permanent, searchable knowledge. It’s perfect for building RAG applications around historical advertising performance.

Retrieving Historical Ad Data with LlamaIndex

Need to compare this month's spending to last year's? Your AI client indexes the output from `ads_get_cpc_metrics`. This means you can query past sessions and ask, 'What was our average spend in Campaign X during Q2?' The system retrieves the historical data points directly from your knowledge base. This is far better than digging through dozens of CSV files. It combines live API results with long-term memory.

Indexing Ad Group and Keyword Configurations

When you run `ads_get_keyword_performance` or `ads_list_campaigns`, the resulting data—including keywords, match types, and associated IDs—gets indexed. This lets your agent answer specific questions like, 'Which ad group had high performance but low bids last month?' using structured API output. The LlamaIndex approach turns operational data into semantic knowledge for advanced querying.

Setup guide

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

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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 Walmart Connect. 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 Walmart Connect Ads MCP in LlamaIndex

You run tools like `ads_get_item_health_report` to generate data, then you index that output. Later, you query the knowledge base using natural language against the indexed ad performance metrics.

The key difference is persistence. Instead of just executing a command (like pausing a campaign with `ads_pause_campaign`), LlamaIndex saves that action's context and results, allowing you to query past decisions.

Yes. You can index the output from `ads_get_cpc_metrics` every few hours. This builds a time-series knowledge graph that you can query against to spot unusual spending patterns or sudden drops in impressions.

You run `ads_get_keyword_performance`, index the resulting table, and then ask specific questions against that indexed knowledge. For example: 'Show me all keywords with a bid over $2.00 that performed poorly last week.'

This server touches campaign configuration details, including keyword texts, match types, bid amounts, and performance metrics such as spend, impressions, and clicks for Walmart Connect Ads.

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