appsflyer · MCP Server

Improvado MCP — Extract Your AppsFlyer Data With One Question

Improvado gives your AI agent direct access to AppsFlyer attribution and mobile marketing data through an MCP server. Query install sources, ROAS, LTV cohorts, and re-engagement performance across all apps in natural language. Works with Claude, ChatGPT, Cursor, and any MCP-compatible tool.

46K+ metrics ·Read & Write access ·500+ platforms ·<60s setup

Read

Read: Pull Any AppsFlyer Attribution Metric Instantly

Skip the AppsFlyer dashboard. Ask your AI agent for install attribution, cohort ROAS, LTV by source, or re-engagement performance across every app, campaign, and date range. The MCP server handles AppsFlyer API calls.

Example prompts

"What's the 30-day ROAS by install source for our iOS app this quarter? Break down paid vs organic."

45 min → 1 min

"Show me D7 and D30 retention rates by acquisition channel. Which channel delivers the highest-quality users?"

1 hr → 2 min

"Compare campaign-level CPI and LTV across all active UA campaigns for Android and iOS over the last 90 days."

3 hrs → 3 min

Works with Claude ChatGPT Cursor +5

Write

Write: Act on Attribution Data Without Leaving Chat

Your AI agent doesn't just read AppsFlyer data — it connects attribution insights to campaign actions. Adjust audience rules, update postback configurations, trigger audience exports, and manage retargeting lists through natural language.

Example prompts

"Export the high-LTV user segment from the last 60 days as a custom audience and push it to Meta Ads."

2 hrs → 10 min

"Update the postback window for the top-performing network to 30 days for in-app purchase events."

1 hr → 5 min

"Create a suppression list of users who made a purchase in the last 14 days and exclude them from the retargeting campaign."

45 min → 5 min

Every action logged · Fully reversible · SOC 2 certified

Monitor

Monitor: Catch Attribution Anomalies and Fraud Early

Set up watches on ROAS, fraud rates, and install quality. Your AI agent monitors AppsFlyer data continuously and flags anomalies — from sudden CPI spikes to fraud cluster patterns — before they damage campaign budgets.

Example prompts

"Alert me if any network's fraud rate exceeds 15% of total installs in a 24-hour period."

Manual → auto

"Every Monday: send a summary of total installs, ROAS by source, D7 retention, and fraud blocked by network."

2 hrs → auto

"Flag any campaign where CPI increased more than 40% week-over-week without a corresponding improvement in LTV."

Manual → auto

Alerts sent to Slack, email, or your AI agent

Full cycle

The Closed Loop: Read → Decide → Write → Monitor

Your AI agent doesn't just surface data — it acts. Adjust pricing, update product descriptions, manage inventory, apply discounts — all through natural language. The MCP server translates intent into API operations.

Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.

Ideate

Launch

Measure

Analyze

Report

Iterate

One conversation. All six phases. Every platform.

The daily grind

Common problems. Direct answers.

Challenge 1

LTV and ROAS Require Multi-Cohort Analysis

The problem

Calculating true LTV by acquisition channel requires cohort analysis across multiple install dates and in-app event windows. AppsFlyer's native cohort reports answer specific predefined questions but can't handle ad-hoc cross-cohort comparisons without building custom reports.

How MCP solves it

Improvado models AppsFlyer cohort data with full event-level granularity. AI agents can query LTV, ROAS, and retention for any cohort combination — install channel, date range, app version, or geography — in a single natural language question.

Try asking

Compare 90-day LTV for users acquired through paid social vs Apple Search Ads across the last three quarterly cohorts.

Answer in seconds

All data sources, one query

Challenge 2

Cross-App Attribution Comparison Requires Multiple Exports

The problem

Teams managing multiple apps can't compare attribution performance across apps without downloading separate exports for each app ID. Building an apples-to-apples comparison of campaign efficiency across a portfolio of apps is a multi-hour manual process.

How MCP solves it

Improvado aggregates AppsFlyer data across all app IDs in a unified data model. AI agents can query and compare attribution metrics across every app in a portfolio in a single question — install sources, ROAS, retention, and fraud rates side by side.

Try asking

Compare D30 ROAS by acquisition channel across all 6 apps in our portfolio for Q1.

Full detail preserved

No data loss on export

Challenge 3

Fraud Detection Insights Don't Reach Campaign Teams Fast Enough

The problem

AppsFlyer's Protect360 identifies fraudulent installs, but the fraud data lives in a separate report from campaign performance data. Media buyers see high install counts and keep spending on fraudulent sources while the fraud report waits to be reviewed.

How MCP solves it

Improvado joins AppsFlyer fraud data with campaign spend data automatically. AI agents surface the real CPI and ROAS after fraud adjustment for every network in real time — so spend decisions are based on quality installs, not gross install counts.

Try asking

What's the fraud-adjusted CPI and ROAS for each network this month? Rank by fraud-adjusted ROAS.

Unified data model

Compare anything side by side

👥 Teams

One Framework. Five Roles. Zero Setup.

Same MCP connection, different workflows for every team member. Each role asks in natural language — the MCP server handles the complexity (rate limits, auth, schema normalization, governance) behind the scenes.

Agency CEO

Portfolio health. Client risk. Revenue signals.

Media Strategist

70% strategy, not 70% ops. Auto campaign QA.

Marketing Analyst

Zero wrangling. Cross-platform. AI narratives.

Account Manager

QBR decks auto-generated. Call prep in 30s.

Creative Director

Performance-to-brief. Predict winners before spend.

FAQ

Common questions

Does AppsFlyer have an MCP server?

AppsFlyer doesn't offer a native MCP server. Improvado provides a hosted MCP server that connects AppsFlyer attribution data to Claude, Cursor, ChatGPT, and any MCP-compatible AI tool. Authentication, Pull API pagination, and data normalization are handled automatically.

What AppsFlyer data can I query through the MCP server?

Install attribution data with media source and campaign attribution, cohort performance (D1, D7, D30, D90 retention and ROAS), LTV by acquisition source and segment, re-engagement campaign performance, fraud detection metrics from Protect360, and custom in-app event data. Improvado normalizes AppsFlyer's Pull API data model across all apps.

Which AI tools work with AppsFlyer through this MCP server?

Any tool supporting the Model Context Protocol — Claude Desktop, ChatGPT, Cursor, Windsurf, Gemini, and custom applications using MCP HTTP transport. Claude is most commonly used due to its native MCP support and strong analytical reasoning for attribution questions — all through Improvado's hosted MCP server.

Can I combine AppsFlyer data with ad platform spend data through the same MCP?

Yes. Improvado connects 1,000+ data sources through the same MCP server. Teams can combine AppsFlyer attribution data with actual spend from Meta, Google, Apple Search Ads, TikTok, and other networks — enabling true blended ROAS calculation without manual data joins.

How does Improvado handle AppsFlyer's Pull API data volume?

Improvado uses AppsFlyer's Pull API with incremental sync to handle large install and event volumes. Data is pre-aggregated by cohort, source, and campaign so AI agents get instant answers even for apps with millions of daily events. Rate limits are managed server-side.

Is mobile attribution data secure through the MCP server?

Yes. Improvado is SOC 2 Type II certified. AppsFlyer API tokens are stored in an encrypted vault. User-level attribution data is handled in compliance with GDPR, CCPA, and ATT framework requirements. Data masking policies can be applied to restrict access to individual device identifiers.

Stop Reporting. Start Executing.

Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.

SOC 2 Type II GDPR 500+ Platforms