How to Use the Walmart Connect Ads MCP in Pydantic AI

Q: How do I check performance metrics for Walmart Connect Ads using Pydantic AI?

Call adsgetcpcmetrics. This tool retrieves spend, impressions, and clicks. Since your agent uses Pydantic, you're guaranteed that the data structure returned is valid every single time.

Q: Can Pydantic AI update Walmart Connect Ads budgets?

Yes. The adsupdatedailybudget tool lets your agent modify campaign spending limits in dollars. Because of runtime validation, you won't get silent failures if the budget input is wrong.

Q: What report types are supported for Walmart Connect Ads with Pydantic AI?

The adsgetitemhealthreport supports many types—like 'placement,' 'category,' and 'brand.' The strength here is that whatever data type comes back, it must pass validation.

Q: How do I manage existing Walmart Connect Ads campaigns with Pydantic AI?

You can use adslistcampaigns to get a list of all campaigns. If you need to stop one, the agent calls adspausecampaign. The whole process is type-safe.

Get guaranteed correctness when running Walmart Connect Ads logic with Pydantic AI.

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Connect Walmart Connect Ads MCP to Pydantic AI

Create your Vinkius account to connect Walmart Connect Ads to Pydantic AI 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 Pydantic AI

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Validated Ad Performance Reporting

Run reports knowing the data structure is correct. The `ads_get_item_health_report` generates performance snapshots for types like 'adGroup' or 'keyword,' and Pydantic validates every field in the response. Furthermore, you can use `ads_get_keyword_performance`, filtering by campaign ID or ad group ID, ensuring that the resulting keyword data adheres strictly to your defined models.

MCP Server for Campaign Control

Control your campaigns with validated actions. You can pause an entire effort instantly using `ads_pause_campaign`. Or, if you need a change in spending limits, the agent calls `ads_update_daily_budget`, guaranteeing the budget amount is correctly parsed. If you're adding new keywords, `ads_add_keywords` requires structured JSON input for text, match type, and bid, which Pydantic validates before sending.

Full Campaign Lifecycle Visibility

The agent can list all running efforts via `ads_list_campaigns`, giving you a clean list of every campaign. If you need to optimize immediately, the combination of listing campaigns and then calling `ads_create_ad_group` lets you build out new ad structures safely. This process minimizes errors because Pydantic validates both the inputs (for creating groups) and the outputs (when listing existing ones).

Setup guide

Set up Walmart Connect Ads MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "walmart-connect-ads-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Walmart Connect Ads tools.",
)

result = await agent.run("List recent Walmart Connect Ads transactions")
print(result.output)

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Common questions about Walmart Connect Ads MCP in Pydantic AI

Call `ads_get_cpc_metrics`. This tool retrieves spend, impressions, and clicks. Since your agent uses Pydantic, you're guaranteed that the data structure returned is valid every single time.

Yes. The `ads_update_daily_budget` tool lets your agent modify campaign spending limits in dollars. Because of runtime validation, you won't get silent failures if the budget input is wrong.

The `ads_get_item_health_report` supports many types—like 'placement,' 'category,' and 'brand.' The strength here is that whatever data type comes back, it must pass validation.

You can use `ads_list_campaigns` to get a list of all campaigns. If you need to stop one, the agent calls `ads_pause_campaign`. The whole process is type-safe.

This server handles financial and keyword advertising data. Specifically, it manages daily budget figures, which must be validated as dollars, alongside campaign IDs and metric performance data.

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