AppLovin MCP. Get instant revenue reports from MAX mediation data.
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…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
AppLovin MCP connects your AI agent directly to AppLovin and MAX mediation data. Pull real-time insights on revenue, impressions, eCPM, and user acquisition performance using natural language prompts.
It lets you track everything from campaign spend via `list_campaigns` to detailed user lifetime value reports.
What your AI agents can do
Get account check
Verifies that your connection credentials for AppLovin are active and working correctly.
Get app discovery report
Pulls performance data specifically for all of your User Acquisition (UA) campaigns in AppDiscovery.
Get max cohort report
Generates detailed reports showing how well users retained over time using MAX cohort analysis.
Instantly retrieve aggregated performance stats for MAX, including eCPM and total impressions.
Get detailed revenue data broken down either by specific users or by individual ad impression.
Generate cohort reports to track how well your app retains users over time.
List all active apps or view performance data for specific UA campaigns in AppDiscovery.
Verify the connection health of your AppLovin account instantly.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
AppLovin MCP: 7 Tools for Ad Metrics
These seven tools allow you to pull everything needed for ad monetization analysis—from listing apps to detailed user revenue reports.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using AppLovin on Vinkius019d7550get account check
Verifies that your connection credentials for AppLovin are active and working correctly.
019d7550get app discovery report
Pulls performance data specifically for all of your User Acquisition (UA) campaigns in AppDiscovery.
019d7550get max cohort report
Generates detailed reports showing how well users retained over time using MAX cohort analysis.
019d7550get max report
Retrieves aggregated performance data for your MAX mediation platform, allowing you to specify date ranges and key columns.
019d7550get user ad revenue report
Calculates revenue figures, giving you the choice between aggregating data per user or per impression.
019d7550list apps
Provides a list of all apps currently tracked within your AppLovin account inventory.
019d7550list campaigns
Retrieves a full list of all active User Acquisition campaigns managed through the system API.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with AppLovin, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AppLovin. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Dashboard fatigue is brutal.
Right now, checking monetization performance requires clicking through five different tabs: one for general MAX metrics, another to filter by campaign type, a third to pull the cohort data, and then exporting two separate sheets—one of impressions, one of revenue. You spend more time managing dashboards than analyzing results.
With this MCP, you simply ask your agent what you need. It handles running `get_max_report` for metrics, pulling `get_user_ad_revenue_report` for the money data, and synthesizing it all into one simple answer. You get the insight without the clicks.
The AppLovin MCP gives you comprehensive insights.
You no longer need to manually cross-reference which apps are active versus which campaigns are running. The agent can use `list_apps` and then immediately check the performance of those listed apps using a query that involves both inventory and campaign data.
It's about connecting the dots instantly. You get the full picture: from knowing what apps you track to seeing how revenue was generated for every user.
What you can do with this MCP connector
Managing ad monetization means juggling a dozen dashboards, each showing only part of the picture. You need to correlate daily revenue with long-term user retention and current campaign performance—and doing that manually is a massive time sink.
This MCP gives your agent a single entry point into all AppLovin data. Instead of exporting CSVs and spending hours in Excel, you talk to your AI client and ask the question: 'What was our Day 7 retention rate last month?' The system handles the complex API calls across multiple data sets—retrieving aggregated performance metrics for MAX mediation or pulling granular revenue reports per user.
It lets you audit campaign spend using AppDiscovery reports while simultaneously checking current app inventory via list_apps. When your agent pulls this data through Vinkius, it structures everything into a readable answer. You get immediate insights on monetization and growth trends without ever leaving the chat window.
019d7550-cf49-7060-a5ee-bbf9f82838e1 
How AppLovin MCP Works
- 1 You prompt your AI client with a natural language question, like 'Show me MAX revenue for last week.'
- 2 The MCP interprets that request, selecting and executing the appropriate tools (e.g.,
get_max_report) and pulling raw data from AppLovin. - 3 The agent synthesizes this disparate information into one clear, summarized answer directly in your chat window.
The bottom line is you skip the dashboard clicks and get a direct, actionable metric summary.
Who Is AppLovin MCP For?
This connector is for Ad Operations Managers and Growth Engineers who are tired of spending evenings manually stitching together data from multiple ad platforms. If your job involves reconciling eCPM changes with campaign spend across different mediation layers, this MCP saves you days.
Using the MCP to quickly audit monetization performance and check trends in metrics like eCPM without having to export files or build custom reports.
Monitoring campaign spend across AppDiscovery using natural language queries while listing available apps via list_apps.
Analyzing user-level revenue and running cohort reports to figure out where the long-term retention bottlenecks are.
What Changes When You Connect
- Stop manually exporting CSVs for eCPM trends; query the
get_max_reportdirectly. You get aggregated performance metrics instantly, saving hours of dashboard work. - Understand long-term value by running the
get_max_cohort_report. This lets you see if Day 1 retention drops off dramatically on Week 3, helping target specific fixes. - Audit campaign spend against revenue using both
list_campaignsand theget_app_discovery_report. You can instantly check if a high-spend campaign is actually delivering profitable users. - Deep dive into monetization by running
get_user_ad_revenue_report. This separates out user-level performance from simple impression counts, giving you true insight into LTV. - Never lose track of your assets again. Use
list_appsto verify which app inventories are active and correctly linked before a major campaign launch.
Real-World Use Cases
The Q3 Performance Audit
The Ad Ops Manager needs to prove quarter-over-quarter revenue growth. They prompt the agent: 'Give me an aggregated MAX report for Q3, focusing on eCPM and total revenue.' The MCP handles running get_max_report across all necessary date ranges, giving them the final numbers in seconds.
Investigating Retention Drop-off
The Product team notices a sudden dip in Day 7 retention. They ask for a cohort report, triggering get_max_cohort_report. The resulting data immediately points to the specific user segment that is failing to stick around.
Verifying Campaign Spend ROI
The UA Specialist needs to check if their latest campaign is worth the budget. They use list_campaigns to confirm activity and then run get_app_discovery_report to see performance, quickly confirming if spend matches revenue.
The Tradeoffs
Running multiple reports sequentially
Manually running a report for 'Yesterday' and then another one for 'Last Week', only remembering to change the date parameter on both calls. This is slow, repetitive, and prone to human error.
→ Group your request into a single prompt: 'Compare MAX performance metrics and revenue between yesterday and last week.' The agent runs the necessary tools in sequence, comparing the results automatically.
Confusing campaign spend with user value
Assuming that because list_campaigns shows a high volume of impressions, the users are profitable. You miss correlating that traffic to actual revenue.
→
Always run get_user_ad_revenue_report after checking campaign status. This forces the agent to link spend (via AppDiscovery data) directly to proven user revenue.
When It Fits, When It Doesn't
Use this MCP if your primary need is diagnostic deep-dives into ad performance metrics: understanding why revenue changed, tracking retention patterns, or auditing a specific campaign's lifecycle. This setup excels at complex data retrieval across disparate sources.
Don't use it if you need real-time dashboard monitoring, continuous predictive modeling, or workflow automation that requires state management outside of a chat session. For those needs, look into dedicated BI platforms or specialized ETL tools. If your goal is simply to list what exists (e.g., just listing apps), the list_apps tool handles that fine, but for complex analysis, you need this MCP.
Common Questions About AppLovin MCP
How do I check my AppLovin account connection using get_account_check? +
Running get_account_check verifies your credentials and confirms the MCP can talk to the platform. This is a quick health check before running any major reports.
Can I see user revenue data with get_user_ad_revenue_report? +
Yes, this tool provides detailed revenue metrics and lets you choose if you want the report aggregated per individual user or by impression count for a different view.
What is the difference between list_apps and get_app_discovery_report? +
list_apps just shows the inventory—a static list of apps you track. get_app_discovery_report, however, pulls dynamic performance data for those apps across your UA campaigns.
Does get_max_cohort_report help with retention? +
Absolutely. The tool generates cohort analysis reports, which are essential for tracking long-term user retention and understanding how many users stick around past the first week.
How do I adjust the date range when using get_max_report? +
You use specific start and end parameters to filter data. This lets you pull aggregated performance metrics for a precise time window, rather than relying on default reporting periods.
What is the difference between list_campaigns and get_app_discovery_report? +
list_campaigns only provides a directory of your active UA campaigns. It tells you the names and statuses, but it doesn't include performance metrics like revenue or impressions.
If I run get_account_check and receive an error, what does that mean? +
An error means your AI client couldn't validate the connection credentials. You'll need to verify both the Report and Management keys in your AppLovin account settings.
Does list_apps track all apps, or just those currently running? +
It lists every app that is actively tracked within your current AppLovin account. It provides a comprehensive inventory of assets you can monitor for monetization.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.