How do I find my Pinterest Ad Account ID?

In your Pinterest Business account, go to the Ads Manager. Your Ad Account ID is usually visible in the URL or in the account settings section.

Can I see performance metrics for specific dates?

Yes! Use the `get_pinterest_analytics` tool and provide the `start_date` and `end_date` parameters along with the columns (metrics) you wish to retrieve.

What metrics can I retrieve?

Common metrics include SPEND_IN_DOLLAR, IMPRESSION, CLICKTHROUGH, REPIN, and TOTAL_CONCLICK. You can provide multiple metrics separated by commas.

Pinterest Ads MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Pinterest Ads
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Pinterest 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 Pinterest Ads "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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About Pinterest Ads MCP Server

Connect your Pinterest Advertising account to any AI agent and take full control of your visual discovery marketing through natural conversation.

Pydantic AI validates every Pinterest Ads tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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

Campaign & Ad Group Oversight — List all campaigns and ad groups to maintain a clear view of your advertising structure.
Analytics Tracking — Fetch detailed performance metrics for specific date ranges to monitor your ROI.
Content Management — List boards and pins to verify your creative assets and organic presence.
Audience Auditing — List saved audiences and product catalogs to ensure your targeting is optimal.
Keyword Analysis — List keywords associated with specific ad groups to refine your search strategy.

The Pinterest Ads MCP Server exposes 10 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 Pinterest Ads to Pydantic AI via MCP

Follow these steps to integrate the Pinterest 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 10 tools from Pinterest Ads with type-safe schemas

Why Use Pydantic AI with the Pinterest Ads MCP Server

Pydantic AI provides unique advantages when paired with Pinterest 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 Pinterest 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 Pinterest Ads connection logic from agent behavior for testable, maintainable code

Pinterest Ads + Pydantic AI Use Cases

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

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

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

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

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

Pinterest Ads MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Pinterest Ads to Pydantic AI via MCP:

get_pinterest_analytics

Get advertising analytics

get_pinterest_campaign

Get details for a specific campaign

list_pinterest_ad_groups

List ad groups

list_pinterest_ads

List Pinterest ads

list_pinterest_audiences

List saved audiences

list_pinterest_boards

List Pinterest boards

list_pinterest_campaigns

List Pinterest ad campaigns

list_pinterest_catalogs

List product catalogs

list_pinterest_keywords

List keywords for an ad group

list_pinterest_pins

List Pinterest pins

Example Prompts for Pinterest Ads in Pydantic AI

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

"List all my active Pinterest ad campaigns."

"How much did we spend on Pinterest ads between 2026-10-01 and 2026-10-15?"

"Show me the pins from my 'Home Decor' board."

Troubleshooting Pinterest Ads MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Pinterest Ads + Pydantic AI FAQ

Common questions about integrating Pinterest 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 Pinterest Ads MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.