How do I find my Adjust API Token?

Log in to your Adjust dashboard, go to **My Profile** or **Account Settings**, and find the **API Token** section. You can copy your existing token or generate a new one there.

Can I check the attribution of a test device?

Yes! Use the `inspect_device` tool and provide the Adjust Device ID (ADID). Your agent will return the current tracker, network, and campaign associated with that device.

Does this server support KPI reporting?

Yes, you can use the `get_kpi_report` tool to retrieve aggregated performance data such as installs, re-attributions, and clicks for your apps.

Adjust MCP Server for Pydantic AI 3 tools — connect in under 2 minutes

Name: Adjust
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 3 Tools SDK

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

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

Connect your Adjust account to your AI agent to unlock professional mobile measurement and attribution insights. From auditing app settings to inspecting device attribution and monitoring key performance indicators (KPIs), your agent handles your mobile growth data through natural conversation.

Pydantic AI validates every Adjust tool response against typed schemas, catching data inconsistencies at build time. Connect 3 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

App Automation — Retrieve and audit technical settings for your mobile applications, including event tokens and partner parameters
Device Inspection — Verify the attribution status of specific devices using their advertising IDs (ADID) for testing and support
KPI Monitoring — Retrieve aggregated performance metrics like installs, clicks, and sessions to monitor app growth
Event Tracking Audit — List active event tokens and verify that your in-app events are correctly configured
Attribution Oversight — Quickly identify which networks and campaigns are driving the most high-value users directly from chat

The Adjust MCP Server exposes 3 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 Adjust to Pydantic AI via MCP

Follow these steps to integrate the Adjust 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 3 tools from Adjust with type-safe schemas

Why Use Pydantic AI with the Adjust MCP Server

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

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

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

Adjust + Pydantic AI Use Cases

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

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

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

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

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

Adjust MCP Tools for Pydantic AI (3)

These 3 tools become available when you connect Adjust to Pydantic AI via MCP:

get_app_settings

Get app configuration

get_kpi_report

Filterable by date. Get aggregated KPI metrics

inspect_device

Inspect device attribution

Example Prompts for Adjust in Pydantic AI

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

"Retrieve the settings for my app with token 'abcdef123456'."

"Inspect the attribution status for ADID '12345-67890'."

"Show me the total installs for last week."

Troubleshooting Adjust MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Adjust + Pydantic AI FAQ

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