Where do I find my Adtraction API Token?

Log in to your Adtraction account, navigate to **Account** > **Settings** > **API**. You can generate or retrieve your unique token there. It will be used in the `X-Token` header.

Can I see my earnings by advertiser?

Yes! Use the `get_stats_by_program` tool. Your agent will retrieve aggregated statistics for each advertiser you are partnered with, including commissions and conversion rates.

Does this support transaction status tracking?

Yes, the `list_transactions` tool provides the current status (Pending, Approved, Denied) for every sale or lead tracked in your account.

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

Name: Adtraction
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 Adtraction 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 Adtraction "
            "(5 tools)."
        ),
    )

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

asyncio.run(main())

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* 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 Adtraction MCP Server

Connect your Adtraction affiliate account to your AI agent to unlock professional performance marketing management. From auditing advertiser programs across multiple categories to tracking real-time transactions and managing your product feeds, your agent handles your affiliate operations through natural conversation.

Pydantic AI validates every Adtraction 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

Program Management — List and retrieve details for available advertiser programs, including commission structures and categories
Transaction Auditing — Retrieve detailed logs of sales and leads to monitor your marketing performance and earnings status
Real-time Statistics — Retrieve performance data broken down by day or by advertiser program directly from chat
Product Feed Access — List and retrieve metadata for advertiser product feeds to support your affiliate content strategy
Channel Oversight — List and manage your approved marketing channels (websites, social media) within the network

The Adtraction 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 Adtraction to Pydantic AI via MCP

Follow these steps to integrate the Adtraction 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 Adtraction with type-safe schemas

Why Use Pydantic AI with the Adtraction MCP Server

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

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

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

Adtraction + Pydantic AI Use Cases

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

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

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

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

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

Adtraction MCP Tools for Pydantic AI (5)

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

get_program_details

Get program metadata

get_stats_by_program

Get performance stats per program

list_channels

List approved media channels

list_programs

List affiliate programs

list_transactions

List affiliate transactions

Example Prompts for Adtraction in Pydantic AI

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

"List all advertiser programs in the 'Fashion' category."

"Show me my performance stats for today."

"Retrieve the latest 5 approved transactions."

Troubleshooting Adtraction MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Adtraction + Pydantic AI FAQ

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