How do I find my Facebook Ad Account ID?

You can find your Ad Account ID in the **Meta Ads Manager**. It's the numeric ID shown in the URL or account selector. Ensure you provide it without the 'act_' prefix.

Can I pause an underperforming campaign using this agent?

Yes! Use the `update_campaign_status` tool and set the status to `PAUSED`. You can also resume it later by setting it back to `ACTIVE`.

Which performance metrics are available in the insights?

The `get_insights` tool provides comprehensive data including impressions, clicks, total spend, reach, CPC (cost per click), CTR (click-through rate), and CPP (cost per purchase).

Facebook Ads MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: Facebook Ads
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Facebook Ads through the 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 Facebook Ads "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())

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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 Facebook Ads MCP Server

Connect your Facebook Ads (Meta Marketing) account to any AI agent and take full control of your advertising campaigns through natural conversation.

Pydantic AI validates every Facebook Ads tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through the 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 Management — List all campaigns, fetch detailed settings, and update statuses (ACTIVE/PAUSED) directly from the cloud
Ad Set & Ad Inspection — Drill down into specific ad sets and ads to review targeting, budgets, and creative details
Performance Insights — Extract granular metrics like impressions, clicks, spend, reach, and CPC to analyze your ROI
Account Overview — Retrieve ad account metadata including balance, currency, and overall account status
Identity Context — Verify the authorized user and access level for the connected marketing token

The Facebook Ads MCP Server exposes 12 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 Facebook Ads to Pydantic AI via MCP

Follow these steps to integrate the Facebook 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 12 tools from Facebook Ads with type-safe schemas

Why Use Pydantic AI with the Facebook Ads MCP Server

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

Facebook Ads + Pydantic AI Use Cases

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

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

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

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

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

Facebook Ads MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect Facebook Ads to Pydantic AI via MCP:

get_ad_account_info

Get basic info for the Facebook Ad Account

get_ad_details

Get details for a specific ad

get_ad_set_details

Get details for a specific ad set

get_campaign_details

Get details for a specific campaign

get_insights

Get performance insights for the Ad Account

get_me

Get current token identity info

list_ad_sets

List ad sets in the Ad Account

list_ads

List ads in the Ad Account

list_campaigns

List campaigns in the Ad Account

update_ad_set_status

Update the status of an ad set

update_ad_status

Update the status of an ad

update_campaign_status

Update the status of a campaign

Example Prompts for Facebook Ads in Pydantic AI

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

"List all active campaigns in my ad account."

"Show me the performance insights for the last week."

"Pause campaign 123456789."

Troubleshooting Facebook Ads MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Facebook Ads + Pydantic AI FAQ

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