How do I find my Amazon Ads API credentials?

You need to create a 'Login with Amazon' application in the Amazon Developer Console to get your Client ID and Client Secret. Then, you generate a Refresh Token. The agent will use these to obtain short-lived Access Tokens.

How do I choose the correct region?

Select the region that matches your target marketplace: **NA** (North America - US, CA, MX, BR), **EU** (Europe - UK, DE, FR, IT, ES, etc.), or **FE** (Far East - JP, AU, SG).

Why do reports take time to generate?

Amazon Ads reporting API is asynchronous. When you request a report using the `request_sp_report` tool, it returns a `reportId`. You must wait a few moments and use the `get_report_status` tool to download the data once it's ready.

Amazon Ads MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Amazon Ads
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Amazon Ads through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Amazon Ads "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Amazon Ads?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Amazon Ads MCP Server

Connect your Amazon Ads account to your AI agent to unlock professional campaign orchestration and performance tracking. From auditing Sponsored Products and Sponsored Brands to generating asynchronous performance reports and managing keyword bids, your agent handles your e-commerce advertising strategy through natural conversation.

Pydantic AI validates every Amazon Ads tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Profile Oversight — Retrieve Amazon Ads profiles to manage campaigns across different global marketplaces
Campaign Orchestration — List and audit Sponsored Products and Sponsored Brands campaigns to monitor active budgets
Ad Group & Keyword Management — List ad groups and targeted keywords to ensure your products appear in the right search results
Performance Reporting — Request and retrieve asynchronous reports to analyze clicks, impressions, and ad spend
Advertising Insights — Quickly identify underperforming keywords or out-of-budget campaigns directly from your chat interface

The Amazon Ads MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI 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 Amazon Ads to Pydantic AI via MCP

Follow these steps to integrate the Amazon Ads MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Amazon Ads with type-safe schemas

Why Use Pydantic AI with the Amazon Ads MCP Server

Pydantic AI provides unique advantages when paired with Amazon Ads through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Amazon Ads integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Amazon Ads connection logic from agent behavior for testable, maintainable code

Amazon Ads + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Amazon Ads MCP Server delivers measurable value.

Type-safe data pipelines: query Amazon Ads with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Amazon Ads tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Amazon Ads and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Amazon Ads responses and write comprehensive agent tests

Amazon Ads MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Amazon Ads to Pydantic AI via MCP:

get_report_status

Check report status

list_profiles

List advertiser profiles

list_sb_campaigns

List Sponsored Brands campaigns

list_sb_keywords

List SB keywords

list_sp_ad_groups

List SP ad groups

list_sp_campaigns

List Sponsored Products campaigns

list_sp_keywords

List SP keywords

request_sp_report

Request performance report

Example Prompts for Amazon Ads in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Amazon Ads immediately.

"List my Amazon Ads profiles."

"Show me the active Sponsored Products campaigns for profile ID '123456'."

"Request a campaign performance report for yesterday (Profile ID '123456')."

Troubleshooting Amazon Ads MCP Server with Pydantic AI

Common issues when connecting Amazon Ads to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Amazon Ads + Pydantic AI FAQ

Common questions about integrating Amazon Ads MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Amazon Ads MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.