Provides tools to scrape Apple App Store data, including app details, search, reviews, and similar apps.
Provides tools to scrape Google Play Store data, including app details, search, reviews, and similar apps.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-store-scraper Search for 'Signal' on Google Play"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server that exposes Google Play and Apple App Store scraping as tools.
Add to your MCP client config (e.g. ~/.kiro/settings/mcp.json):
{
"mcpServers": {
"store-scraper": {
"command": "npx",
"args": ["-y", "mcp-store-scraper"],
"disabled": false,
"autoApprove": [
"gplay_app", "gplay_search", "gplay_reviews", "gplay_similar",
"appstore_app", "appstore_search", "appstore_reviews", "appstore_similar"
]
}
}
}Related MCP server: mcp-appstore
Tool | Description |
| Get app details by package name |
| Search apps |
| Get app reviews |
| Get similar apps |
Tool | Description |
| Get app details by bundle ID or numeric ID |
| Search apps |
| Get app reviews |
| Get similar apps |
This package is powered by two great open source libraries:
google-play-scraper by @facundoolano — scrapes app data from the Google Play Store
app-store-scraper by @facundoolano — scrapes app data from the Apple App Store
Get details of an app from Apple App Store
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Numeric app ID | |
| lang | No | en-us | |
| appId | No | Bundle ID, e.g. com.example.app | |
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It accurately indicates a read operation ('Get details') but does not mention that results may be localized by country/language or that an identifier is required. This is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action and object, making it efficient. However, it is arguably too terse to carry the necessary context for a tool with four parameters and no annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema or annotations, the description should explain more about return contents and identifier requirements. It only says 'details', which is insufficient for an agent to know what data is returned or how to identify the app.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 50% (only appId has a description), and the description adds no parameter semantics. It leaves ambiguity about whether id or appId is required and how lang/country defaults affect results, failing to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'details of an app from Apple App Store', clearly distinguishing it from siblings like appstore_search (search) and appstore_reviews (reviews). It precisely names the platform and the resource being retrieved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing app details, but it does not explicitly state when to prefer this over appstore_search or appstore_app siblings. No exclusions, prerequisites, or alternative tool names are mentioned, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get reviews of an app from Apple App Store
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Numeric app ID | |
| page | No | Page number (1-10) | |
| sort | No | recent | |
| appId | No | Bundle ID | |
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'Get reviews' and offers no information on pagination (page 1-10), sorting options (recent/helpful), country filtering, return format, or rate limits. It does not mislead but provides almost no transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or redundancy, which is efficient. It loses a point because the brevity borders on under-specification for a tool with multiple parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given five parameters and no output schema, the description is too sparse. It does not explain how reviews are returned, the meaning of pagination and sorting, or which app identifier to use. The description leaves critical invocation details unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 60%, and the tool description adds nothing about parameters. The relationship between 'id' (numeric app ID) and 'appId' (bundle ID) is ambiguous, and 'country' lacks a schema description. The description fails to clarify these ambiguities.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it retrieves reviews of an app from the Apple App Store, a specific verb and resource. This clearly distinguishes it from the Google Play sibling tools (e.g., gplay_reviews) by platform, so the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The platform (Apple App Store) is explicitly identified, making the intended context clear versus Google Play alternatives. However, there is no explicit 'use when' or 'don't use when' guidance or mention of alternative tools, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search apps on Apple App Store
| Name | Required | Description | Default |
|---|---|---|---|
| num | No | Number of results | |
| lang | No | en-us | |
| term | Yes | Search term | |
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It simply says 'Search apps' with no information about read-only behavior, pagination, or result details. It does not mislead but fails to disclose any behavioral traits beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, but it is under-specified. It is not tautological, yet it lacks front-loaded key details such as 'by term' or mention of country/language options.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is still incomplete. It does not mention that results depend on country and language, nor does it describe what is returned (e.g., app metadata, count). With no output schema, the description should provide more context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (term and num have descriptions, lang and country do not). The tool description adds no parameter information, failing to compensate for the missing schema descriptions or clarify defaults and required parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: 'Search apps on Apple App Store.' This distinguishes it from Google Play search and other app-specific tools, though it does not explicitly differentiate from sibling search tools like appstore_similar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention use cases, prerequisites, or exclusions. The only implication is that it is for Apple App Store searches, but this is not explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get similar apps from Apple App Store
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Numeric app ID | |
| appId | No | Bundle ID | |
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Get similar apps' and does not mention response format, whether an app identifier is required, potential errors, or any constraints. This is insufficient for safe and effective use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is concise and easy to parse, though it sacrifices detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, no annotations, and only a very brief description. With three parameters, two of which are identifier variants, the description is far too minimal to enable confident invocation. It fails to explain how the parameters interact or what the returned data represents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema partially describes id and appId, but the description adds no meaning to the parameters. It does not explain the relationship between id and appId, whether one is required, or how country affects results. The country parameter lacks a description, and the tool description does not compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('similar apps from Apple App Store'), and it is distinguishable from sibling tools like appstore_search, appstore_app, and appstore_reviews. However, it does not explicitly mention that similarity is relative to an input app identifier, leaving slight ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as appstore_search or appstore_app. The description implies usage when similar apps are needed, but it does not provide context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get details of an app from Google Play Store
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language code | en |
| appId | Yes | Package name, e.g. com.example.app | |
| country | No | Country code | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It merely states the action without any context about what 'details' includes, error handling, rate limits, or response format. The description is too thin to inform the agent of expected behavior beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and directly states the core purpose. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should clarify what details are returned (e.g., title, version, rating). It also lacks guidance on how this differs from similar tools. Given the simplicity of the tool, the description is incomplete for an agent to fully understand the expected output and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all three parameters (appId, lang, country), so the schema already provides the necessary parameter semantics. The description adds no extra parameter information, but the baseline of 3 applies given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieving app details from the Google Play Store. It uses a specific verb (Get) and resource (app details from Google Play Store), and it is distinct from sibling tools like gplay_search, gplay_similar, and gplay_reviews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need details of a specific app by appId, but it does not explicitly state when to use this vs. alternatives like gplay_search or gplay_similar. No exclusions or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get reviews of an app from Google Play Store
| Name | Required | Description | Default |
|---|---|---|---|
| num | No | Number of reviews | |
| lang | No | en | |
| sort | No | newest | |
| appId | Yes | Package name | |
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Get reviews', implying a read operation, but omits any detail about return format, pagination, sorting behavior, or potential limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that succinctly conveys the core purpose without any fluff or redundancy. It is appropriately sized for its function and immediately understandable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite being a simple tool, it has 5 parameters with enums and defaults, but no output schema. The description fails to explain what a review entry looks like, how to control sorting/language/country, or any other behavioral nuances, leaving significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention any parameters, while the schema covers only 40% of them descriptively (appId and num). The highly relevant parameters like lang, sort, and country are left unexplained, and the description adds no compensatory meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get') and resource ('reviews of an app'), and identifies the platform ('Google Play Store'). This distinguishes it from siblings like 'appstore_reviews' and other gplay_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given about when to use this tool versus alternatives such as gplay_app or appstore_reviews. The platform mention provides only implicit context, but there are no exclusions or decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search apps on Google Play Store
| Name | Required | Description | Default |
|---|---|---|---|
| num | No | Number of results (max 250) | |
| lang | No | en | |
| term | Yes | Search term | |
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It only implies a read-only operation but gives no details about return format, pagination, rate limits, or other behaviors. This is a significant gap for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero wasted words. It is as concise as possible while still conveying the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, absence of an output schema, and incomplete parameter documentation, the one-line description is insufficient for an agent to understand the tool's full behavior or expected output. The tool is simple, but the description leaves too many gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%: only 'term' and 'num' have descriptions, while 'lang' and 'country' are undocumented. The tool description adds no parameter semantics at all, failing to compensate for the gaps in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'search' and the resource 'apps on Google Play Store', which differentiates it from sibling tools like gplay_reviews or gplay_similar. However, it lacks any additional scope or qualifiers, so it does not fully reach the specificity of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as gplay_app or gplay_similar. It only states the basic action, without any exclusions, prerequisites, or context for when to prefer this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get similar apps from Google Play Store
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | en | |
| appId | Yes | Package name | |
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only says 'Get similar apps' without mentioning return format, limitations, language/country effects, or any side effects. This is too sparse for an agent to anticipate tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded, clear sentence with no redundant words. It states the core purpose immediately and is appropriately concise for its simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description must cover more ground. It omits parameter semantics, result shape, and usage context, making it incomplete for an agent to confidently invoke the tool, despite the simple 3-parameter interface.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only appId has 'Package name'). The description adds no parameter information, failing to clarify the meaning or role of 'lang' and 'country' or how they affect results. With low schema coverage, the description needed to compensate but did not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('similar apps from Google Play Store'), clearly distinguishing it from siblings like gplay_search, gplay_app, and especially appstore_similar. It is unambiguous about the platform and action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Google Play similar-app lookups, and the sibling names provide some context, but it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or conditions. No alternative tools are referenced.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.1.0appstore_appappstore_reviewsappstore_searchappstore_similargplay_appgplay_reviewsgplay_searchgplay_similarEach tool targets a distinct store and action, with clear prefixes (gplay_ vs appstore_) and specific purposes (search, app details, similar, reviews). There is no overlap or ambiguity between tools.
The naming follows a consistent prefix-plus-suffix pattern (store name + action). However, the suffixes are not all verbs (e.g., 'app' and 'reviews' are nouns), so it deviates slightly from a strict verb_noun convention.
With 8 tools total, split evenly between two app stores, the count is well-scoped for a store scraping purpose. Each tool serves a distinct function without redundancy.
The set covers core search, details, similar, and reviews for both major app stores. Minor gaps like top charts or category browsing are absent, but the essential scraping workflows are well covered.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
All HasData scraping tools in one MCP server: Google, TikTok, Instagram, maps, e-commerce and more.
One MCP server for 180+ live web-data APIs returning clean JSON from sites that block scrapers.
Search 77,000+ MCP servers ranked by real adoption data to find the right one for any task.
MCP server for Appcircle mobile CI/CD platform.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/LucasMonteiro1/mcp-store-scraper'
If you have feedback or need assistance with the MCP directory API, please join our Discord server
