Where do I find my AdButler API Key?

Log in to your AdButler dashboard, go to **Settings** > **API Settings**. You can generate your Secret API Key there. Note that API access requires the API add-on to be enabled.

Can I see real-time impressions and clicks?

Yes! Use the `get_report` tool to retrieve up-to-the-minute statistics for your campaigns, zones, or entire network.

Does this server support creative management?

Yes, you can use the `list_creatives` tool to audit and manage the ad assets associated with your account.

AdButler MCP Server for Pydantic AI 5 tools — connect in under 2 minutes

Name: AdButler
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 5 Tools SDK

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

    result = await agent.run(
        "What tools are available in AdButler?"
    )
    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 AdButler MCP Server

Connect your AdButler account to your AI agent to unlock professional ad serving management and real-time reporting. From auditing publisher inventory to monitoring campaign delivery and analyzing click-through rates (CTR), your agent handles your ad operations through natural conversation.

Pydantic AI validates every AdButler tool response against typed schemas, catching data inconsistencies at build time. Connect 5 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

Inventory Management — List publishers and ad zones to maintain full control over where your advertisements are displayed
Campaign Oversight — List and retrieve details for self-serve campaigns, including statuses and targeting rules
Performance Reporting — Retrieve instant statistics on impressions, clicks, and revenue across your entire network
Creative Auditing — List and manage ad creative assets to ensure your visual content is always up-to-date
Revenue Optimization — Quickly identify top-performing zones or underdelivering campaigns directly from your chat interface

The AdButler MCP Server exposes 5 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 AdButler to Pydantic AI via MCP

Follow these steps to integrate the AdButler 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 5 tools from AdButler with type-safe schemas

Why Use Pydantic AI with the AdButler MCP Server

Pydantic AI provides unique advantages when paired with AdButler 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 AdButler integration code

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

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

AdButler + Pydantic AI Use Cases

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

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

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

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

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

AdButler MCP Tools for Pydantic AI (5)

These 5 tools become available when you connect AdButler to Pydantic AI via MCP:

get_performance_report

Provide a specific metric type and optional dates. Retrieve aggregated ad performance metrics (impressions, clicks, CTR) across zones and campaigns in AdButler

list_campaigns

Retrieve a list of active and pending self-serve advertising campaigns in AdButler

list_creatives

Retrieve the library of ad assets (banners, videos) stored in your AdButler account

list_publishers

Retrieve the full list of publishers managing ad inventory in your AdButler network

list_zones

Requires Publisher ID. Retrieve the active ad zones (placements) linked to a specific AdButler publisher

Example Prompts for AdButler in Pydantic AI

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

"List all publishers in my AdButler network."

"Show me the performance report for the last 7 days."

"List all active zones for publisher ID 12345."

Troubleshooting AdButler MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

AdButler + Pydantic AI FAQ

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