Connecting Attribution Data to AI Agents: How EndFrame's MCP Server Works

AI agents are transforming how teams analyze data, write reports, and make decisions. But an AI agent that cannot reach your actual data is just generating plausible-sounding guesses. The gap between a useful AI workflow and a frustrating one is almost always data access, and for marketing teams, that means getting attribution data out of the dashboard and into the tools where AI can work with it.

The data access problem

Most marketing dashboards are built for humans. They render charts, tables, and filters that work well when a person is clicking through them. But AI agents cannot click through a dashboard. They need structured data returned through an API, ideally one designed for the way AI tools consume information. Without that, teams end up copy-pasting numbers into prompts, which is slow, error-prone, and defeats the purpose of automation.

What MCP solves

MCP, the Model Context Protocol, is an open standard that gives AI agents a structured way to connect to external tools and data. Instead of building one-off integrations or scraping HTML, an AI agent with MCP access calls well-defined tools that return clean, structured responses. Think of it as a universal adapter between your data and any AI system that supports the protocol.

How the EndFrame MCP server works

EndFrame's MCP server implements JSON-RPC 2.0 and exposes eight tools that cover the data most AI workflows need from an attribution platform:

• List and search campaigns with filters for status, domain, and date range.
• Retrieve visit data with session details, source parameters, and engagement metrics.
• Pull analytics breakdowns by language, screen resolution, source, and time period.
• Query engagement KPIs including average scroll depth and average engagement time.
• Check domain connection status and campaign coverage.
• Access lead data with source path and campaign context intact.

Each tool accepts structured parameters and returns JSON, so AI agents can query exactly what they need without parsing HTML or navigating a UI.

Real workflows this enables

With MCP access, AI agents can generate weekly campaign performance summaries automatically, flag campaigns where engagement time drops below a threshold, compare traffic quality across channels without a human pulling the data, and feed attribution context into larger AI-powered decision systems. The key shift is that the AI works with real numbers from your workspace, not hallucinated estimates.

The best AI integrations do not replace your dashboard. They give your data a second life in workflows the dashboard was never designed to serve.

Getting started

The MCP server is available as a toggleable add-on in the EndFrame marketplace. Enable it, create an API key from the settings panel, and configure your AI agent to connect to the endpoint. No custom code, no engineering project. Your attribution data becomes queryable by any MCP-compatible AI tool within minutes.