Appier MCP. Analyze campaign performance and segment data in chat.
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…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Appier helps your AI agent manage marketing campaigns and analyze predictive audiences directly in chat. Instead of jumping into complex dashboards, you can list active campaigns, check conversion metrics, or pull performance analytics like ROAS for specific segments using natural language.
What your AI agents can do
Get audience
Retrieves detailed information for one specific target audience.
Get campaign
Fetches the full configuration details for a single marketing campaign.
Get campaign analytics
Provides performance metrics like CTR, CPC, and ROAS for a specific campaign.
List every running CrossX or AIQUA marketing campaign and check its specific configuration details.
Retrieve predefined, AI-generated audiences and view the criteria used to predict user behavior.
Pull full analytics for any campaign, including CTR, CPC, ROAS, and conversion counts.
List all active machine learning prediction engines, such as churn risk or purchase probability models.
View a record of historical conversion events like purchases or signups across your accounts.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Appier with 8 Tools
Use these tools to access specific marketing data points like segment lists, campaign configurations, or performance metrics across Appier.
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 Appier on Vinkius019d7550get audience
Retrieves detailed information for one specific target audience.
019d7550get campaign
Fetches the full configuration details for a single marketing campaign.
019d7550get campaign analytics
Provides performance metrics like CTR, CPC, and ROAS for a specific campaign.
019d7550list audiences
Lists all available target audiences configured in the system.
019d7550list campaigns
Retrieves a list of every active marketing campaign running through Appier.
019d7550list conversions
Shows a record of all tracked conversion events, like purchases or signups.
019d7550list predictions
Lists the names and statuses of active AI predictive models (e.g., Churn Risk).
019d7550list segments
Gets a list of all configured user segments used for targeting.
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 Appier, 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 Appier. 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 8 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The Dashboard Hop
Right now, checking performance means jumping between tabs: you open Appier for campaign IDs; then you switch to your CRM to check user segments; after that, you might have to pull reports into a spreadsheet just to get the ROAS number. It's constant context switching and copy-pasting.
With this MCP, you keep everything in chat. You prompt your agent with a request—like 'What was the conversion rate for Q3'? The agent handles all the data retrieval across campaigns, segments, and conversions, giving you one clean answer.
Getting campaign metrics using `get_campaign_analytics`
Before this MCP, pulling an analytics report for a specific campaign meant logging into the system and manually running a report on that campaign's ID. You had to wait for the dashboard to generate the data.
Now, you ask your agent directly: 'Show me the ROAS for Campaign XYZ.' The agent calls `get_campaign_analytics`, retrieves the metrics instantly, and presents them in conversation. It’s immediate context awareness.
What you can do with this MCP connector
This MCP connects your chat environment to Appier's full suite of marketing data. You get direct access to predictive audiences, segment sizes, and real-time campaign performance without ever leaving your conversation interface. It handles everything from listing active campaigns to pulling detailed analytics like ROAS and CPC for any given effort.
You can also query the status of ML models—checking things like churn risk or purchase probability—and track historical conversion events, such as signups or purchases. If you're looking for an all-in-one data connection that handles campaign performance alongside predictive modeling, Vinkius hosts this MCP so your agent can access it from any compatible client.
019d7550-30ed-7157-b7b9-71cad2a0c992 
How Appier MCP Works
- 1 Subscribe to this MCP and provide your Appier API Key and API URL.
- 2 Your agent calls the relevant function, for example,
list_campaignsto see what's running. - 3 The system returns structured data containing metrics or segment details that your agent then interprets and presents in chat.
The bottom line is you get real-time Appier marketing data piped into natural conversation flow.
Who Is Appier MCP For?
Growth Marketers, Data Analysts, Marketing Leadership. Anyone who gets frustrated having to switch between the app dashboard, a spreadsheet, and their chat window just to check campaign performance or segment size.
Checks ROAS and CPC across campaigns continuously without leaving their strategy document.
Parses active ML predictive models and segmentation rules right alongside the code they're writing.
Prompts their agent to summarize overall campaign statuses and total conversions before a board meeting.
What Changes When You Connect
- Check ROAS and CPC metrics instantly. You don't have to navigate the Appier dashboard just to know if a campaign is profitable. The
get_campaign_analyticstool pulls this data directly. - Understand your users better by viewing segments. Use
list_segmentsorget_audienceto see exactly what criteria predict user behavior before you launch an ad. - Run predictive checks on demand. Quickly list and analyze ML predictions with
list_predictions, letting you know if your churn model is active without opening a separate platform tab. - Track revenue history effortlessly. Use
list_conversionsto pull concrete numbers of purchases or signups, giving immediate proof of ROI for any campaign reviewed viaget_campaign_analytics. - Save time listing campaigns. Instead of manually checking dashboards, run
list_campaignsand instantly get a summary of all active marketing efforts.
Real-World Use Cases
Quarterly Review Prep
A Marketing Leader needs to summarize Q3 performance before a meeting. They prompt the agent: 'What was the overall ROAS for Q3 campaigns?' The agent runs list_campaigns and then pulls detailed metrics using get_campaign_analytics, summarizing it all in one response.
Audience Refinement
A Data Analyst needs to confirm if their new 'High LTV' segment is ready for testing. They use list_segments to check the name, then run get_audience on it to pull the underlying criteria and size.
Post-Campaign Audit
An E-commerce Team needs to know if a recent promotion actually led to high-value purchases. They use list_conversions to review historical events, cross-referencing the dates with a specific campaign ID retrieved via get_campaign.
Model Health Check
A Product Manager wants assurance that their churn prediction model is live. They simply ask: 'What predictive models are running?' The agent runs list_predictions and reports the status of all ML engines immediately.
The Tradeoffs
Checking metrics manually
Opening Appier, navigating to Campaign X's dashboard, finding the ROAS graph, writing down the number, and then pasting it into a document.
→
Just ask your agent. Use get_campaign_analytics and provide the campaign ID you want metrics for. It pulls the data directly without any manual clicks.
Forgetting segment context
Running a query about conversions, but not knowing if those conversions belong to the 'High Value' or 'Low Engagement' user group.
→
Always start by listing and checking your segments using list_segments first. Then, use that specific segment name when analyzing performance via get_audience.
Over-relying on one metric
Only looking at the conversion count from list_conversions and assuming everything is fine, ignoring spend or cost.
→
Cross-reference list_conversions results with performance metrics pulled using get_campaign_analytics. This gives you both volume (conversions) and efficiency (ROAS).
When It Fits, When It Doesn't
Use this MCP if your primary job involves connecting predictive audience data to concrete campaign performance. You need to know not just if a user converted, but why they might convert and how much that conversion is worth relative to the ad spend. Don't use it if you are only managing internal tasks or non-marketing related operations—you don't need list_campaigns for that. If your goal is simply to create a new campaign, stick to Appier’s native dashboard tools. But if the goal is analysis and reporting across existing campaigns, this MCP handles it all.
Common Questions About Appier MCP
How do I use `list_audiences` with this MCP? +
list_audiences shows you every target audience available. You call it first to see the names, and then you can pass a specific name to get_audience if you want details on one of them.
Can I check ROAS using `get_campaign_analytics`? +
Yes. You need to specify which campaign ID you want metrics for, and the tool will return performance data including Return on Ad Spend (ROAS) alongside CPC.
Does this MCP track recent purchases? Use `list_conversions`. +
Yes. The list_conversions tool pulls a record of tracked events like signups or actual purchases, giving you the volume data needed for reporting.
What is the best way to check predictive models? Use `list_predictions`. +
list_predictions lists all active ML prediction engines. This lets you confirm if a model like 'Churn Risk' is running before building any strategy around it.
If I'm testing my credentials, how can I use `list_campaigns` without running a full analytics report? +
You simply call list_campaigns. This action validates your API key and connection immediately. It returns the names and IDs of all campaigns visible to your agent; it doesn't pull any performance data, so it’s safe for initial setup checks.
What should I do if `get_audience` fails because the audience ID is incorrect? +
The MCP will return a specific error code and message detailing why the request failed. You'll need to cross-reference the provided ID with a successful call to list_audiences. That confirms the ID exists before you try retrieving its details.
Is there a difference between running `list_audiences` and using `list_segments`? +
Yes, they serve different purposes. While list_audiences shows defined marketing targets, list_segments gives you every configured user group based on raw data rules. Use list_segments when your agent needs to analyze underlying behavioral criteria.
If I need performance metrics for hundreds of campaigns, how does `get_campaign_analytics` handle rate limits? +
The MCP handles standard API throttling automatically. If you exceed the allowed calls within a set time frame, your agent will pause and alert you to wait before trying again. You'll get clear error messages guiding when you can resume.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.