- Best for
- google play store app search and metadata retrieval, app metadata enrichment and structured extraction, multi-criteria app filtering and ranking
- Type
- MCP Server · Free
- Score
- 31/100
- Best alternative
- AWS MCP Servers
- Agent-compatible
- Yes — MCP protocol
Capabilities8 decomposed
google play store app search and metadata retrieval
Medium confidenceEnables semantic and keyword-based search across the Google Play Store catalog via MCP protocol, returning structured app metadata including ratings, reviews, pricing, and installation counts. Implements a standardized tool interface that LLM agents can invoke to discover apps matching user queries without requiring direct API credentials or authentication handling by the client application.
Exposes Google Play Store search as a standardized MCP tool that LLM agents can invoke directly, abstracting away authentication and API management while maintaining structured metadata output compatible with agent reasoning loops
Simpler integration than building custom Google Play API wrappers because it uses MCP's standard tool-calling protocol, allowing any MCP-compatible LLM to search apps without SDK-specific code
app metadata enrichment and structured extraction
Medium confidenceParses and structures raw Google Play Store app data into standardized fields (title, description, rating, review count, price, category, developer, permissions, screenshots, etc.) for downstream consumption by agents or applications. Uses MCP's resource-based response format to deliver consistent, queryable metadata that agents can reason over without additional parsing or normalization steps.
Delivers Play Store metadata in MCP's standardized resource format, enabling agents to reason over app data using consistent field names and types without custom parsing logic for each app
More reliable than scraping Google Play directly because it uses official data sources and handles pagination/rate-limiting server-side, reducing client-side complexity and breakage from UI changes
multi-criteria app filtering and ranking
Medium confidenceSupports filtering and sorting app search results by multiple criteria (rating threshold, price range, minimum install count, category, language support, developer reputation) and returns ranked results based on relevance, popularity, or user-defined scoring. Implements filtering logic server-side to reduce data transfer and enable agents to narrow results before processing.
Implements server-side filtering and ranking to reduce payload size and computation on the client/agent side, allowing LLMs to work with pre-filtered result sets that are more likely to match their intent
More efficient than client-side filtering because it reduces network transfer and allows the server to optimize queries against the Play Store data source, whereas alternatives require fetching full result sets and filtering in-memory
app review aggregation and sentiment analysis
Medium confidenceRetrieves and aggregates user reviews for apps, including review text, ratings, and metadata (reviewer name, review date, helpful votes). May include basic sentiment classification or summary statistics to help agents understand user sentiment without reading individual reviews. Implements pagination to handle apps with thousands of reviews.
Aggregates reviews server-side with optional sentiment summarization, allowing agents to understand user feedback at scale without processing thousands of individual review texts
More scalable than parsing reviews client-side because aggregation happens on the server, reducing bandwidth and computation required by the agent to synthesize user sentiment
app category and taxonomy browsing
Medium confidenceProvides access to Google Play Store's app categories and subcategories, enabling agents to explore the app ecosystem by category hierarchy. Implements a browsable taxonomy that agents can traverse to discover categories or filter searches by category constraints. Returns category metadata including app counts, popularity, and subcategory relationships.
Exposes Play Store's category taxonomy as a browsable MCP resource, allowing agents to understand the app ecosystem structure and use categories as a navigation primitive for discovery
Simpler than hardcoding category lists because it reflects the live Play Store taxonomy and can be updated server-side without client changes
developer profile and app portfolio retrieval
Medium confidenceRetrieves information about app developers including their profile, contact information, published apps, and developer reputation metrics. Enables agents to understand developer context and discover related apps from the same publisher. Implements caching to avoid redundant developer lookups across multiple app queries.
Aggregates developer information across their app portfolio, allowing agents to assess developer reputation and discover related apps without separate lookups for each app
More efficient than querying individual apps to find developer info because it provides a single developer profile endpoint that includes all published apps and aggregated metrics
app version history and changelog tracking
Medium confidenceRetrieves version history and changelogs for apps, including release dates, version numbers, and update descriptions. Enables agents to understand app evolution, identify recent changes, and assess update frequency. Implements changelog parsing to extract structured information about bug fixes, features, and improvements.
Parses and structures changelog data server-side, allowing agents to reason about app maintenance and development velocity without manual text parsing
More reliable than scraping changelogs from the Play Store UI because it accesses structured data directly and handles pagination for long version histories
app permissions and privacy policy analysis
Medium confidenceRetrieves app permissions (requested Android/iOS permissions), privacy policy text, and data handling practices. Enables security-focused agents to assess privacy risks and understand what data apps access. Implements permission categorization (dangerous, normal, signature) to help agents identify high-risk permissions.
Categorizes and structures permission data with risk assessment, allowing agents to quickly identify privacy concerns without manual permission analysis
More comprehensive than simple permission listing because it includes privacy policy retrieval and risk categorization, giving agents a holistic view of app data practices
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓LLM application developers building app recommendation systems
- ✓AI agents that need to answer user questions about mobile apps
- ✓Teams building cross-platform discovery tools that include mobile app search
- ✓Developers building app comparison or recommendation UIs
- ✓Security-focused teams analyzing app permissions and privacy practices
- ✓Data engineers building datasets of mobile app metadata for analysis
- ✓Recommendation engine builders who need to apply business logic to app rankings
- ✓Teams building filtered app discovery experiences for specific user segments
Known Limitations
- ⚠Search results limited to publicly available Google Play Store data; cannot access unpublished or region-restricted apps
- ⚠No real-time app update notifications or change tracking — metadata reflects current Play Store state only
- ⚠Rate limiting may apply if MCP server receives high-volume concurrent search requests
- ⚠Cannot retrieve sensitive app data like revenue, download analytics, or developer contact information
- ⚠Metadata structure is fixed by the MCP server implementation — cannot customize fields returned without modifying server code
- ⚠Screenshots and images are returned as URLs only; no local caching or image processing included
Requirements
Input / Output
UnfragileRank
UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.
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MCP server: google-play-mcp
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