Adikteev MCP. Predict churn risk and manage audience segments in chat.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Adikteev MCP Server manages app retargeting and predicts user churn. Connect your AI agent to list, create, and manage custom audience segments, track campaign performance data, and retrieve churn probability scores for your mobile user base.
What your AI agents can do
Create segment
Builds a new audience segment for retargeting campaigns.
Get churn scores
Calculates and returns a list of users ranked by their probability of leaving the app.
Get reporting
Retrieves detailed data on how well your retargeting campaigns are performing.
Creates and manages custom user segments for targeted ad campaigns.
Retrieves a list of users ranked by their probability of abandoning the app.
Pulls detailed performance data for all active retargeting campaigns.
Retrieves a list of all existing audience segments associated with your account.
Retrieves the necessary technical metadata and IDs for audience management.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
Adikteev MCP Server: 5 Tools for Growth Marketing
Use these five tools to build segments, predict churn, and analyze campaign performance data from Adikteev.
019d7547create segment
Builds a new audience segment for retargeting campaigns.
019d7547get churn scores
Calculates and returns a list of users ranked by their probability of leaving the app.
019d7547get reporting
Retrieves detailed data on how well your retargeting campaigns are performing.
019d7547list companies
Gets the necessary ID for the company running the app.
019d7547list segments
Shows all currently existing audience segments.
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 Adikteev, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ 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
What you can do with this MCP connector
You're talking to the Adikteev MCP Server, so your AI agent can manage your mobile growth and predict who's gonna bounce. You can connect your agent to build, track, and analyze all your custom audience segments, check campaign performance, and get churn scores for your user base.
Build audience groups: Use create_segment to build a new audience segment for retargeting campaigns, and list_segments to see every segment already set up.
Calculate churn risk: Run get_churn_scores to get a list of users ranked by how likely they are to leave the app.
Analyze campaign ROI: Use get_reporting to pull detailed data on how well your retargeting campaigns are doing.
List user segments: You can check out all the audience segments associated with your account using list_segments.
Get company IDs: Running list_companies gets the necessary technical IDs you need for audience management.
How Adikteev MCP Works
- 1 Subscribe to the Adikteev server and input your API credentials (email and password).
- 2 Tell your agent what you need—for example, 'Find the highest-risk users' or 'List all cart abandoners.'
- 3 Your agent runs the required tools (
get_churn_scores,list_segments, etc.) and presents the data conversationally.
The bottom line is, you talk to your AI agent, and it handles the data retrieval and analysis from Adikteev.
Who Is Adikteev MCP For?
Growth marketers and user retention specialists need this. If you're tired of logging into Adikteev, running five different reports, and manually correlating segment lists with churn data, this server handles the whole flow. It gives you the data you need to fix retention issues before they become revenue problems.
Uses the agent to automatically manage audience segment creation via create_segment and audit campaign performance using get_reporting.
Runs get_churn_scores to identify specific, high-risk users, allowing them to trigger personalized re-engagement workflows.
Checks retargeting ROI by pulling campaign data via get_reporting and ensuring the most profitable user segments are being targeted.
Pulls historical campaign data and company metadata using get_reporting and list_companies for B2B intelligence tools.
What Changes When You Connect
- Identify users at risk before they leave. The
get_churn_scorestool ranks your user base, telling you exactly who needs attention right now. - Keep your campaigns focused. You can use
list_segmentsandcreate_segmentto manage precise audience groups, ensuring your ads reach the right people. - Track real money. The
get_reportingtool pulls campaign performance data, so you know exactly which retargeting efforts are giving the best ROI. - Simplify data gathering. Instead of running multiple reports, you can use
list_companiesto pull the technical metadata needed for segmentation, all through your agent. - Audit your efforts quickly. You can audit your entire retargeting strategy and identify high-value user groups using the combined insights from
list_segmentsandget_reporting.
Real-World Use Cases
Finding the best users to re-engage
A retention specialist needs to find users who downloaded the app but haven't opened it in 30 days. They tell their agent to run list_segments for 'Inactive Users (30d)' and then run get_churn_scores on that list. The agent returns a prioritized list of the highest-risk users, telling the specialist exactly who to target.
Optimizing campaign spend
A UA manager wants to know if the last ad campaign was worth the cost. They ask the agent to use get_reporting for the last quarter. The agent pulls the data, showing total users reached and the average re-engagement rate. The manager can then ask to focus on ROI for a specific campaign.
Setting up a new targeting group
A growth marketer knows a specific group of high-value purchasers need a dedicated ad campaign. They ask the agent to first use list_companies to get the necessary ID, and then use create_segment to build the 'High Value Purchasers' segment for retargeting.
Investigating data gaps
A data analyst needs to compare current user activity against historical data. They first use get_reporting to pull baseline performance, and then use list_segments to ensure all necessary historical user groupings are accounted for in the current build.
The Tradeoffs
Running manual, separate reports
Logging into Adikteev, running 'Segments Report,' then opening a new tab to run 'Campaign Performance,' and manually cross-referencing the numbers to find the most profitable users.
→
Just ask your agent. The agent runs list_segments and get_reporting in sequence, synthesizing the data and showing you the correlation immediately. You don't move tabs; you talk to the agent.
Guessing the right segment ID
Trying to manually remember or guess the exact technical ID needed to filter user data, which often leads to incomplete or incorrect user lists.
→
Use list_companies first to ensure you have the correct technical metadata, and then use list_segments to verify the exact segment IDs before you try to build a new segment with create_segment.
Ignoring churn risk
Focusing only on current campaign metrics (get_reporting) and failing to proactively identify users who are already leaving the app.
→
Always check the user health first. Run get_churn_scores to identify the top 5% of at-risk users. Then, use create_segment to build a 'High Churn Risk' segment and retarget them immediately.
When It Fits, When It Doesn't
Use this server if your workflow requires correlating user segment data with campaign performance and retention risk. You need to know who is leaving and why your ads are working. Use get_churn_scores and get_reporting together to build a full picture. Don't use this if your only goal is simple data viewing—just pulling raw lists of users. For simple listing, list_segments is enough. If you need to create a segment, you must use create_segment after running list_companies to validate the required metadata.
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.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
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 5 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Tracking user segments and campaign performance is a mess of dashboards.
Today, checking your app's health means jumping between Adikteev's segmentation view, the campaign performance dashboard, and the user list. You have to copy the segment name from one tab and paste it into another to run a report. It's slow, and you always lose context.
With the Adikteev MCP Server, you just talk to your agent. You ask, 'Show me the performance of the 'Cart Abandoners' segment.' The agent runs the necessary tools, correlates the segment data with the campaign metrics, and gives you one clean answer.
Adikteev MCP Server: Get actionable insights from `get_churn_scores`.
Before, spotting at-risk users meant analyzing usage patterns manually, cross-referencing login dates with purchase history. It was a spreadsheet exercise that took hours and was always incomplete.
Now, your agent runs `get_churn_scores` and hands you a ranked list of users who are most likely to quit. It’s instant, precise, and tells you exactly where your retention efforts need to go.
Common Questions About Adikteev MCP
How do I use `get_churn_scores` with Adikteev MCP Server? +
You tell your agent to run get_churn_scores and specify the app bundle. The agent returns a ranked list of users based on their probability of churning, making it easy to target the highest-risk users first.
Does `list_segments` help me manage retargeting? Adikteev MCP Server? +
Yes, list_segments shows you every segment you currently have. You can then ask the agent to use create_segment to build a new one based on a specific criteria.
What data does `get_reporting` provide for campaign performance? +
get_reporting pulls detailed campaign performance data. This lets you monitor key metrics like ROI and engagement across all your active campaigns.
What is the purpose of `list_companies` in Adikteev MCP Server? +
list_companies retrieves the required technical metadata and ID for the company running the app. You need this ID to ensure the agent can target the data correctly.
Can I create a segment without using `list_segments` first? +
While you can call create_segment directly, it's safer to first run list_segments to see what segments already exist and avoid accidental duplicates or conflicts.
How do I use `create_segment` to build a new audience segment? +
You provide the segment criteria directly. You specify the target audience characteristics, like user actions or demographics, that you want to include in the new segment.
Is there a way to check the usage limits when calling `get_reporting`? +
The system will report any rate limits encountered during the call. You must check the API documentation for specific usage quotas or adjust your calling frequency.
What kind of metadata does `list_companies` return? +
It returns essential technical metadata, including the necessary company ID. This ID is required to accurately scope and manage your audience segments.
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.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
More in this category
Offerslook
Manage performance marketing via Offerslook — track offers, advertisers, and affiliates directly from your AI agent.
Ontraport
Manage marketing and sales via Ontraport — list contacts, track campaigns, and monitor transactions directly from any AI agent.
Google Analytics 4
Understand your website and app traffic with event-based analytics that reveal user behavior, conversions, and growth trends.
You might also like
Moonscan (Moonbeam Network Explorer)
Access Moonbeam blockchain data via Moonscan — check GLMR balances, track transactions, and inspect smart contracts directly from any AI agent.
Duolingo
Track language learning progress on Duolingo — view profiles, streaks, XP, leaderboards and dictionary hints.
Alpha Vantage
Access stock market data via Alpha Vantage — get real-time quotes, time series, technical indicators and crypto/forex data from any AI agent.