# Appbot MCP for AI Agents MCP

> Appbot gives you deep insights into user feedback for your mobile app. It lets your AI client analyze reviews—whether from iOS or Android—to track sentiment, identify bug reports, and uncover key topics instantly. You can filter massive amounts of text by star rating, country, or specific keywords without leaving your chat interface.

## Overview
- **Category:** customer-support
- **Price:** Free
- **Tags:** sentiment-analysis, app-reviews, user-feedback, customer-insights, mobile-apps, rating-tracking

## Description

Appbot lets you turn thousands of app store reviews into actionable product data. Instead of manually sifting through a spreadsheet of complaints, you talk to your agent and it handles the heavy lifting. You can programmatically pull in raw review text, analyze the overall tone—is it positive, negative, or mixed?—and categorize every piece of feedback by common themes. It even tracks changes across different app versions so you know exactly when a new release caused problems. Because Vinkius hosts Appbot alongside 4,000 other MCPs, you connect your AI client once and get access to this review analysis tool plus hundreds of others, making it the single source for all your operational data.

## Tools

### get_account_info
Pulls Appbot account details and confirms your connection status with the service.

### get_review_details
Provides complete, granular information for a single, specific user review.

### get_reviews_by_custom_topic
Collects all reviews that fall under a custom topic you've set up in your Appbot account.

### list_apps
Displays every application name and ID currently tracked by the team within Appbot.

### list_countries
Lists all geographical regions available for filtering review data to understand local market feedback.

### list_custom_topics
Retrieves the list of user-defined thematic categories you've set up in the Appbot dashboard.

### list_languages
Shows all languages supported by Appbot for accurate sentiment analysis and filtering.

### list_reviews
Lists reviews for a specific app, allowing optional filters by keywords, star rating, or general sentiment to narrow results quickly.

### list_topics
Retrieves the list of standard themes identified within app reviews using Appbot's built-in AI analysis.

### list_versions
Detects and lists all specific application versions that have received user feedback in the reviews.

## Prompt Examples

**Prompt:** 
```
What were the main complaints about the app last week?
```

**Response:** 
```
**Weekly Sentiment Report: Last 7 Days**

*   **Overall Trend:** Slightly more negative (Avg. Star Rating: 3.1/5)
*   **Top Complaint Category:** Performance Issues (28% of negative reviews)
    *   *Key Bug:* App crashes during payment processing.
    *   *Affected Version:* v4.1
*   **Trending Topic:** 'Syncing' is mentioned 30% more often than the week prior, suggesting a recent backend change broke something.
```

**Prompt:** 
```
Show me the most common topics for my US audience.
```

**Response:** 
```
**Top Topics in Reviews (USA)**

Based on reviews from the last 30 days, here are the top three themes:

1.  **Performance:** Mentioned frequently, often linked to slow loading times.
2.  **User Interface:** Users report difficulty finding settings menus.
3.  **Payment Flow:** Specific complaints about required multi-factor authentication steps.

*Action:* Focus on simplifying the user flow for payments in v4.2.
```

**Prompt:** 
```
Compare feedback from Canada versus the UK.
```

**Response:** 
```
**Comparative Review Analysis**

| Feature | Canada (CA) | United Kingdom (UK) |
| :--- | :---: | :---: |
| **Sentiment** | Mostly neutral, focusing on features.
| Negative, centered on stability. |
| **Top Issue** | Missing integration with local banking apps. | App crashes when switching between tabs. |

*Insight:* The UK audience is focused on immediate reliability; the Canadian audience wants more advanced feature parity.
```

## Capabilities

### List all tracked applications
See every app managed within Appbot by running list_apps.

### Retrieve specific user reviews
Get the full text and details for any single review using get_review_details. It's great for deep dives into specific complaints or praise.

### Filter by custom topics
Pull together all reviews associated with a pre-defined group of keywords or themes via get_reviews_by_custom_topic.

### Find reviews across different countries
Understand your global audience by filtering reviews using the list_countries tool to narrow down results by region.

### Analyze all standard and custom themes
List common topics identified in user feedback, whether they're built-in standards or custom themes defined in your dashboard (list_custom_topics).

### Narrow down reviews by keywords and sentiment
Run a comprehensive search for reviews using list_reviews, letting you filter by star rating, specific words, or the overall sentiment.

## Use Cases

### A new feature is failing in the market.
The Product Manager asks: 'What are the top three pain points regarding the checkout flow?' The agent uses list_reviews and get_reviews_by_custom_topic to return a prioritized list of complaints, showing that 70% of issues relate to payment gateway compatibility.

### Support team needs to know if an issue is spreading.
A Support Lead asks: 'Check all reviews from France and Italy mentioning 'sync error' over the last week.' The agent uses list_languages, list_reviews, and get_review_details to provide a geo-specific report, indicating the problem started after a specific app version was pushed.

### Developers need help prioritizing bug fixes.
The App Developer asks: 'List all reviews for our Android app version 3.2 that mention 'crashes' or 'slow.' What is the sentiment?' The agent uses list_versions and list_reviews to deliver a quantitative count of technical bugs versus general complaints.

### Understanding seasonal shifts in user focus.
The Product Manager asks: 'What are the most common topics mentioned in reviews globally during Q4?' The agent uses list_topics and list_countries to analyze trends, showing that 'holiday gift exchange' became a dominant theme months ahead of usual reporting.

## Benefits

- Pinpoint the exact cause of frustration. You don't just see 'negative'; you use list_reviews to filter by keywords, instantly finding out if users hate a specific button or feature.
- Manage global feedback in one place. Using list_countries lets your agent group reviews from different regions, letting you compare how 'Performance' is discussed in Germany versus Canada.
- Go deeper than simple star ratings. By using get_reviews_by_custom_topic, you can pull together all comments related to 'Login Issues,' regardless of whether the user gave 1 or 5 stars.
- Evaluate releases instantly. When a new version drops, use list_versions and list_reviews to track feedback specifically for that build, letting developers know exactly what needs fixing right now.
- Consolidate all data sources. Because Vinkius hosts Appbot with thousands of other MCPs, you keep your workflow centralized—you don't need a separate dashboard just for reviews.

## How It Works

The bottom line is, your AI client handles the API calls. You just ask questions about your user feedback, and it returns structured insights immediately.

1. First, connect Appbot to your AI client and provide the necessary API credentials.
2. Next, ask your agent a question. For example: 'Show me all the negative reviews for the last two versions in the UK.'
3. Your agent runs the relevant tools (like list_reviews or get_review_details) and presents you with filtered data, sentiment summaries, and topic breakdowns.

## Frequently Asked Questions

**How does Appbot help me find specific bugs in user reviews?**
Appbot lets you run focused searches using list_reviews. You can combine filters like 'star rating less than 3' and a keyword (like 'crash') to pull only the bug reports. This cuts through generic complaints so developers know exactly what needs fixing first.

**Can Appbot analyze reviews from different countries at once?**
Yes, it can. You use list_countries and list_reviews to group feedback by region. This is critical for seeing if a feature works correctly across your global user base or if the issue is localized to one market.

**Is Appbot better than just reading our internal support tickets?**
Appbot adds vital context that support tickets lack. It gives you the public perception—what users *think* about your product, not just what they told a human agent. You can identify emerging problems before they hit your ticket queue.

**How do I find out if a new app version caused complaints?**
You use list_versions to pinpoint the exact build number and then run reviews against it. This immediate feedback loop means you don't have to wait weeks for manual reports; you know what broke right after deployment.

**Does Appbot just track positive comments, or can it find problems?**
It finds everything. You control the sentiment filter when running reviews, so you can specifically pull negative or mixed feedback. This ensures your focus stays on addressing pain points, not celebrating praise.

**Can Appbot compare themes across multiple apps I run?**
Yes. By listing all apps first and then running topic analysis against each one, you can see if a common theme (like 'login') is impacting your whole product suite or just one specific app.