Appier MCP. Analyze campaign performance and predict audience behavior.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Appier MCP Server. Connects your AI agent directly to Appier marketing data. Use natural language to list campaigns, check ROAS metrics, retrieve predictive audiences, and track conversions without leaving your chat client.
Manage marketing performance and segment data in real time.
What your AI agents can do
Get audience
Gets specific details for a named audience segment.
Get campaign
Gets detailed information about a specific marketing campaign.
Get campaign analytics
Gets performance metrics and analytics for a specific campaign ID.
Retrieves a list of all active campaigns configured in Appier.
Pulls detailed configuration and status information for one named campaign.
Generates analytics, including ROAS and CPC, for a specific campaign ID.
Retrieves a list of all defined target audiences within the Appier system.
Pulls specific data and details for a single, named audience segment.
Lists all configured user segments and running machine learning prediction models.
Lists all types of conversion events that have been tracked (e.g., signups, purchases).
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
Appier MCP Server: 8 Tools for Marketing Analytics
These eight tools let your AI agent access Appier data to list campaigns, retrieve segment details, calculate performance metrics, and track conversions.
019d7550get audience
Gets specific details for a named audience segment.
019d7550get campaign
Gets detailed information about a specific marketing campaign.
019d7550get campaign analytics
Gets performance metrics and analytics for a specific campaign ID.
019d7550list audiences
Lists all available target audiences for selection.
019d7550list campaigns
Lists all active marketing campaigns configured in Appier.
019d7550list conversions
Lists all types of conversion events tracked by the system.
019d7550list predictions
Lists all available AI prediction models (e.g., Churn, Purchase Propensity).
019d7550list segments
Lists all configured user segments and segment criteria.
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 4,700+ 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
Connect your AI agent to Appier to manage marketing data. You can use natural language to list all active campaigns configured in Appier and pull full performance metrics, like ROAS and CPC, for any specific campaign ID. You can also get detailed info on a single campaign using get_campaign. To handle audiences, you can list all available target audiences with list_audiences, or grab specific details for one named audience segment using get_audience.
You can list all user segments and running machine learning prediction models with list_segments, which lets you view segment criteria and prediction statuses. For conversions, you can list all types of conversion events tracked by the system using list_conversions, and you can also view historical conversion events like signups or purchases.
When you need to know what's working, you can list all available AI prediction models using list_predictions. Finally, you can get performance metrics and analytics for a specific campaign ID using get_campaign_analytics.
How Appier MCP Works
- 1 Subscribe to the Appier MCP Server and input your Appier API Key and API URL.
- 2 Your AI client sends a natural language request (e.g., 'What is the ROAS for cmp_q3rtg?').
- 3 The server executes the necessary tool (like
get_campaign_analytics) and returns the formatted data directly to your chat.
The bottom line is that your AI agent executes complex, multi-step marketing data queries using plain conversation.
Who Is Appier MCP For?
Growth Marketers who need to track ROAS and CPC across multiple campaigns without leaving their strategy docs. Data Analysts who need to parse ML model rules and segmentation criteria alongside their code. Marketing Leadership who needs quick, synthesized summaries of campaign status and overall conversions before a meeting. E-commerce Teams needing to dynamically track high-value conversions based on predictive segments.
Uses get_campaign_analytics to track ROAS and CPC metrics across campaigns continuously, keeping the data visible within their workflow.
Uses list_predictions and list_segments to parse active ML models and segmentation rules directly alongside data analysis code.
Uses the agent to prompt summaries of overall campaign statuses and total conversions before leadership meetings.
Uses get_audience to identify specific, high-value user segments for targeted campaigns.
What Changes When You Connect
- See real-time campaign performance. Use
get_campaign_analyticsto pull full metrics (ROAS, CPC, Conversions) for any campaign without leaving your chat. - Understand your users better. Use
list_segmentsandget_audienceto see exactly which predictive segments are most likely to convert. - Manage campaign status fast. Run
list_campaignsto get a full list of active campaigns, thenget_campaignto drill down on configuration details. - Track business results instantly. Use
list_conversionsto see what events are counted as conversions, andget_campaign_analyticsto track their volume. - Know your risks ahead of time. Run
list_predictionsto list active ML models like Churn Risk, allowing you to target at-risk users proactively. - Centralize data access. Instead of logging into separate dashboards, your AI agent pulls data from
list_audiences,list_segments, andlist_predictionsall in one conversation.
Real-World Use Cases
Determining campaign spend effectiveness.
The marketing team needs to know if the 'High LTV Predict' campaign is worth the ad spend. They ask their agent to run get_campaign_analytics for that specific campaign. The agent returns the ROAS (e.g., 310%) and CPC, allowing the team to immediately decide if they should scale up or pause the ad spend.
Identifying potential churn risks.
The Account Manager notices a dip in engagement. They prompt the agent to run list_predictions. The agent reports the 'Churn Risk Model' is running. The manager then uses the model's output to pull a list of high-risk users via get_audience, generating a targeted re-engagement email list.
Auditing segment definitions.
The Data Analyst needs to validate if a new segment, 'Lapsed Purchasers,' is properly defined. They first use list_segments to see the existing criteria, then run get_audience to confirm the segment size and the exact rules applied.
Summarizing performance before a meeting.
The Marketing Director has five campaigns to review. Instead of opening five different dashboards, they ask the agent to list_campaigns and then prompt for a summary of overall conversions and key metrics across the top three, saving 20 minutes of manual dashboard clicking.
The Tradeoffs
Treating the tools as simple database lookups.
Calling list_campaigns and then manually copy-pasting the campaign IDs into a spreadsheet to calculate total ROAS in Excel. This is slow and doesn't account for real-time changes.
→
Let your agent run list_campaigns to get all IDs, then send a single prompt asking the agent to execute get_campaign_analytics for all of them, compiling the totals automatically.
Ignoring data dependencies.
Running get_audience for a segment without first verifying the segment's criteria using list_segments. You might pull data for a segment that is outdated or improperly defined.
→
Always start by running list_segments to verify the segment definition. Then, use get_audience to pull the data for that verified segment.
Focusing only on current metrics.
Only checking ROAS using get_campaign_analytics and missing the bigger picture. You don't know why the ROAS changed.
→
Cross-reference the performance data. Use get_campaign_analytics first, then use list_conversions to check the conversion definition, and finally, use list_predictions to see if a predictive model suggests a change in strategy.
When It Fits, When It Doesn't
Use this if you need to tie marketing actions directly to measurable outcomes and predictive data. If your goal is to calculate ROAS, compare segments, or identify users at risk, this server works. Don't use it if your need is simply to generate creative copy, draft emails, or manage files outside of marketing metrics. If you only need to list a set of static assets, a simple file management tool is better. If you only need to analyze historical data that isn't tied to a live campaign or segment, a general data warehouse connector might be sufficient. But if the data is Appier data, you need this.
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.
Available Capabilities
Dashboard fatigue shouldn't require 15 clicks.
Today, checking campaign performance means jumping between the Appier dashboard, the analytics report, and the segment manager. You click on the campaign, copy the ID, open the analytics tab, and then you have to manually check the segment criteria to figure out if the data is even relevant. It's a copy-paste nightmare that takes forever.
With the Appier MCP Server, you just ask your agent. You say, 'What's the ROAS for the High LTV Predict campaign?' Your agent runs `get_campaign_analytics` and pulls in the relevant segment data, giving you the final answer—ROAS and performance—in a single chat bubble.
Appier MCP Server: Get audience and campaign metrics in chat.
Forget logging into the Appier platform just to check if 'Abandoned Cart Rescue' is running. You use `list_campaigns` to confirm its status and then `get_campaign_analytics` to pull the performance metrics. The entire process happens without opening a single new tab.
It's not just about seeing the data; it's about the workflow. You get immediate, actionable answers in the context where you're already working, which is a massive shift.
Common Questions About Appier MCP
How do I use the `list_campaigns` tool to see what campaigns we have? +
Run list_campaigns to get a list of all active campaigns. The output includes the campaign ID and name, which you then use with get_campaign or get_campaign_analytics for deeper analysis.
What is the difference between `list_segments` and `list_audiences`? +
Use list_segments to see the raw, configured user segments and their rules. Use list_audiences when you need the actual, current list of target audiences that are active for immediate use.
Can I get ROAS using `get_campaign_analytics`? +
Yes, get_campaign_analytics pulls the full performance metrics. You simply name the campaign ID and specify that you need the Return on Ad Spend (ROAS) or CPC.
Does the server track purchases using `list_conversions`? +
Yes, list_conversions lists all tracked conversion events. If purchases are tracked, you'll see 'purchase' listed there, confirming the data source for conversion metrics.
How do I use `get_audience` to check the size of a segment? +
The get_audience tool returns the segment size immediately. This metric tells you exactly how many users fit the criteria you pass in, helping you gauge the potential reach of a campaign.
If I get an error running `get_campaign_analytics`, what should I check? +
Check the campaign ID and the date range you provided. Incorrect IDs or overlapping dates are the most common causes of errors. The tool output will usually point you to the specific failure point.
Which tool should I use to find out what kind of predictions are available, like churn? +
Use list_predictions to see all active ML models. This tool lists the names and basic descriptions of predictions like 'Churn Risk' or 'Purchase Propensity' that Appier supports.
How can I list the conversion events using `list_conversions`? +
list_conversions pulls a list of every tracked conversion type. You can see if events like 'signups' or 'demo requests' are being successfully recorded and tracked by Appier.
Can my AI agent create new predictive models in Appier? +
No. The MCP server is designed natively for reading data, fetching performance stats, analyzing segments, and understanding configurations. Creating complex models still requires the Appier Enterprise Console to ensure ML model safety.
How fast can I generate a campaign ROI report before a meeting? +
In a few seconds. Tell your agent 'Fetch analytics for my top 3 active campaigns' and the AI will invoke the analytics endpoint, process the CPC, CTR, and ROAS data, and output a clean executive summary in whatever format you ask.
Can the agent tell me how big a specific prediction segment is? +
Yes. If an audience ID or segment ID is known, the agent uses the 'get_audience' tool to fetch size estimations, AI criteria, and generation metrics—informing you immediately if your targeted audience size is large enough to launch.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
More in this category
Goaffpro
Manage affiliates, track referral orders, and oversee commissions via AI agents with Goaffpro.
Benchmark Email
Automate email marketing via Benchmark Email — manage contacts, lists, and campaigns directly from any AI agent.
Minutemailer
Email and SMS marketing — manage contacts, lists, and templates via Minutemailer.
You might also like
CHATFLY
Manage AI chatbots and knowledge bases via CHATFLY — train bots on custom data and track conversations directly from any AI agent.
Venue
Manage event venues with booking calendars, client contracts, and catering coordination for wedding and conference spaces.
Caiyun AI Translate / 彩云小译
Popular high-precision machine translation — translate text lists and detect languages via AI.