How do I find my Measured API Key?

You can find your API Key in the Measured platform settings or by contacting your Measured Customer Success Manager (CSM).

What is an incrementality score?

It measures the true causal impact of your ad spend on business outcomes, going beyond standard last-click attribution.

Is my marketing data secure?

Absolutely. Your token is encrypted at rest and injected securely at runtime.

Measured MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Measured
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

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

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Measured MCP Server

Connect your Measured account to any AI agent and take full control of your marketing incrementality and performance data through natural conversation.

Pydantic AI validates every Measured tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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

Incrementality Insights — Access true causal impact scores across all your marketing channels
Performance Tracking — Monitor spend, revenue, and ROAS metrics from over 300 managed integrations
Channel Orchestration — List and inspect performance data for specific channels like Facebook, Google, or Amazon
Automated Reporting — Retrieve performance summaries, insights, and automated reports instantly

The Measured MCP Server exposes 8 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 Measured to Pydantic AI via MCP

Follow these steps to integrate the Measured 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 8 tools from Measured with type-safe schemas

Why Use Pydantic AI with the Measured MCP Server

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

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

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

Measured + Pydantic AI Use Cases

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

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

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

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

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

Measured MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Measured to Pydantic AI via MCP:

get_campaign_performance

Get performance for a specific campaign

get_incrementality_scores

Get incrementality scores across channels

get_insights

Get marketing insights

get_performance_by_channel

Get performance metrics for a specific channel

get_performance_summary

Get a unified performance summary

list_channels

g. Facebook, Google Ads). List all marketing channels tracked by Measured

list_integrations

List managed integrations

list_reports

List available performance reports

Example Prompts for Measured in Pydantic AI

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

"List all active marketing channels in Measured."

"Show performance for Facebook Ads last month."

"What are the latest marketing insights?"

Troubleshooting Measured MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Measured + Pydantic AI FAQ

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