Supercharge your AI with Adikteev. Analyze user segments and predict churn risk.
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Adikteev connects professional app retargeting and user retention insights directly into your workflow. Manage custom audience segments, retrieve campaign performance data, or access churn probability scores—all without leaving your chat client.
This MCP helps you monitor the full mobile growth ecosystem using natural conversation.
What your AI can do
List companies
Gets a list of companies you are associated with, providing technical IDs needed for audience management.
List segments
Retrieves a current list of all existing audience segments managed in the Adikteev account.
Create segment
Builds a new, defined audience segment for use in future retargeting campaigns.
You can list or create specific audience segments needed for targeted app campaigns.
It retrieves probability scores that flag which users are most likely to stop using the app soon.
You get detailed reports on how well past campaigns performed, tracking key engagement metrics.
The tool lists existing companies and retrieves necessary technical metadata for segment setup.
Ask an AI about this
Compatible AI Apps
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Adikteev: 5 Tools for App Growth Marketing
These five tools let you scope companies, list existing segments, create new audiences, check performance reports, or retrieve user churn scores.
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 Adikteev on VinkiusList Companies
Gets a list of companies you are associated with, providing technical IDs needed for audience management.
List Segments
Retrieves a current list of all existing audience segments managed in the Adikteev...
Create Segment
Builds a new, defined audience segment for use in future retargeting campaigns.
Get Churn Scores
Pulls specific probability scores to identify which users are likely to stop using...
Get Reporting
Retrieves detailed performance data on past retargeting campaigns and their overall...
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Claude AI
Open Claude Settings
Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
Add Custom Connector
Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:
https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp
Replace [YOUR_TOKEN_HERE] with your token from
cloud.vinkius.com. For OAuth-protected servers, expand Advanced
settings to add credentials.
Start a conversation
Open a new chat. The Adikteev integration is available immediately — no restart needed.
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.
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Start with Adikteev, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
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- Works with Claude, ChatGPT, Cursor, and more
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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Adikteev. 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 connection provides 5 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Managing audience segments used to feel like a full-time job.
Right now, setting up targeted campaigns means bouncing between four different tools. You pull the list of companies from one dashboard, export that data, paste it into a spreadsheet to clean up IDs, then manually define segments in another UI, and finally, you run the campaign report weeks later just to see if anyone cared.
With this MCP, your agent handles the whole process through chat. You just tell it what you want to target—whether that's 'all high-value users' or 'companies with ID 1234'—and it manages the segment definition and scope using `list_companies` and `create_segment`. The result is immediate, actionable data in your conversation window.
Adikteev MCP gives you instant access to campaign performance.
Manually auditing retargeting efforts used to mean waiting for the weekly report—a process that often missed key spikes or sudden drops. You'd spend hours cross-referencing engagement metrics against your initial segment definition, hoping nothing was wrong.
Now, you can ask your agent to pull `get_reporting` data at any time. It gives you a real-time view of performance trends, letting you spot anomalies and prove campaign ROI without the wait or the headache.
What your AI can actually do with this
You can connect Adikteev to your AI agent to handle complex app retargeting and user retention work. Think of it like having a dedicated marketing analyst available 24/7, who speaks plain English. Your agent manages everything from setting up custom audience segments for specific campaigns to monitoring overall performance and finding out exactly which users are at risk of leaving.
When you're working inside the Vinkius catalog, your AI client handles this entire mobile growth cycle through simple conversation, letting you audit retargeting efforts and identify high-value user groups on demand.
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Here's how it actually works
The bottom line is, your AI agent runs complex marketing analyses using only natural language prompts.
First, subscribe to this MCP and plug in your Adikteev API credentials (email and password).
Next, give your AI client a specific request, like 'List all segments for my top-tier users' or 'What is the churn score for bundle X'.
Finally, the tool executes the action via Adikteev and feeds you the data—whether it’s segment lists, performance metrics, or risk scores—right in the chat.
Who is this actually for?
This MCP is for the Growth Marketer who spends too much time manually building segment lists and cross-referencing performance dashboards. If you're tired of copy-pasting data between Adikteev, Google Sheets, and your BI tool just to figure out why retention dropped last month, this one’s for you.
You automate audience segment management and run campaign performance audits without logging into a separate dashboard.
You retrieve churn scores instantly to trigger personalized re-engagement workflows for at-risk users.
You monitor retargeting ROI and quickly identify the most profitable user segments directly from your chat interface.
What Changes When You Connect
Stop guessing about retention. Using get_churn_scores, you instantly identify high-risk users, allowing your team to launch targeted re-engagement campaigns before the user even notices they're leaving.
Manage audiences faster than ever. You can use create_segment to build new, precise groups based on complex criteria—all through a simple chat command instead of navigating multiple UI forms.
Quickly prove campaign value. Need to know if your last retargeting push actually worked? Run get_reporting to pull detailed data on ROI and engagement rates right away.
Never lose scope again. The list_companies tool gives you the necessary technical IDs, ensuring that any segment or report you run is tied to the correct corporate entity.
Keep your finger on the pulse. By using list_segments, you get a clean rundown of every existing audience group, helping prevent redundant segmentation efforts.
See it in action
The App Store Optimization Check
A UA manager needs to know if their latest ad campaign reached the correct user pool. They ask their agent to use list_companies first, then get_reporting, and finally check segment overlap using list_segments. This confirms they hit the target audience without wasting ad spend on irrelevant groups.
The Proactive Retention Alert
A retention specialist runs a prompt asking for users with high risk. The agent uses get_churn_scores to pull the list, allowing the specialist to manually trigger an incentive program before those users hit zero engagement.
The New User Onboarding Flow
A growth marketer wants to create a segment for 'users who used feature X but never purchased.' They use create_segment with specific criteria, formalizing the hypothesis instantly and making sure the retargeting ads hit the right people.
The Data Audit Cleanup
A data analyst needs a full overview of all current segments before starting a new project. Running list_segments provides an immediate, comprehensive list, preventing them from accidentally duplicating or missing key user groups.
The honest tradeoffs
Trying to manually link data sources
Copying the campaign dates from a Google Sheet into Adikteev's UI and then running a separate query for segment lists. This process is slow, error-prone, and requires multiple logins.
Instead, use your agent to manage the workflow. First, check scope with list_companies, then run get_reporting for campaign metrics, and finally cross-reference that data against segments using a single prompt.
Segmenting without context
Creating a segment just because it sounds useful ('People who clicked the 'About Us' page'). Without proper validation, this group might be too small or inaccurate to target profitably.
Before creating anything, use list_segments and then ask the agent to check the related performance metrics via get_reporting. This ensures your new segment is backed by real data.
Overlooking the user lifecycle
Only focusing on 'new users' and ignoring those who have been active but are slipping away. You might spend money advertising to people who were already lost.
Always check for risk first. Use get_churn_scores to prioritize your efforts, making sure you focus resources only on the most valuable, at-risk users.
When It Fits, When It Doesn't
Use this MCP if your primary bottleneck is connecting ad campaign data and audience segmentation logic into a single, conversational workflow. You need to validate hypotheses—like 'Will this segment perform better than that one?'—using measurable outcomes like churn scores or ROI reports. Don't use it if you are simply looking for raw API documentation or need to build a complex dashboard visualization from scratch; those require dedicated BI tools. However, if your goal is iterative refinement and rapid testing of marketing hypotheses, this MCP provides the critical bridge between data retrieval (using list_companies and list_segments) and actionable insight (get_churn_scores).
Questions you might have
How do I start using the Adikteev MCP with `list_companies`? +
You first ask your agent to run list_companies. This pulls a list of all companies associated with your account, giving you the technical metadata required before building any segments or running reports.
What is the best way to check user risk using `get_churn_scores`? +
Simply ask your agent for 'the churn scores for my app.' It returns a ranked list of users, making it easy to identify who needs immediate attention.
Can I use `create_segment` before running reports? +
Yes. You define the segment first using create_segment. Once that's done, you can then ask for performance data specifically related to that newly created audience group.
Do I need to run `list_segments` before running a report? +
No. While list_segments shows what exists, the agent doesn't require you to manually list them first. You can just ask for 'the performance of all my segments,' and it handles the process.
Do I need to run `list_companies` first before using `create_segment`? +
Yes, you should confirm your company ID first. Running list_companies ensures your MCP connects to the right account. This prevents errors when your agent tries to create a segment in the wrong system.
How do I manage API rate limits if I use `get_churn_scores` frequently? +
Adikteev may impose usage caps on API calls. If your agent hits a limit, it returns an explicit error code. You’ll need to pause and retry the request later or check the dedicated Adikteev dashboard for current limits.
What is the data freshness when I get campaign performance using `get_reporting`? +
The reporting data reflects real-time or near real-time activity. While it updates quickly, always check the Adikteev documentation for the exact sync interval to guarantee absolute accuracy.
When should I use `list_segments` versus checking segments in the UI? +
Use list_segments when you need an automated inventory of all your current audience definitions. It’s faster and better for scripting than reading the user interface, helping you track all existing segments quickly.
How do I get my Adikteev API account? +
You must contact your Adikteev Account Manager to have them enable API access for your account. Once enabled, you can use your standard login credentials (email and password) to authorize the agent.
What is a Churn Score? +
A churn score ranks app users by their probability of leaving. Adikteev provides these in 'buckets' from 1 to 10, where 10 represents the highest risk of churn.
How do I create a new audience segment? +
Use the create_segment tool and provide your companyId, a name, and a description. Your agent will create the segment in Adikteev and provide a segmentId for device ID uploads.
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