MCP (Model Context Protocol) server for Applyra. It connects your App Store and Google Play keyword data to AI assistants like ChatGPT, Claude, Cursor, Codex, VS Code Copilot, and more.
mcp-server is an MCP project maintained in the applyra-io/mcp-server repository. The maintainer describes its purpose as “MCP (Model Context Protocol) server for Applyra. It connects your App Store and Google Play keyword data to AI assistants like ChatGPT, Claude, Cursor, Codex…”. Read the project documentation for the complete scope.
The documented npm package is @applyra/mcp-server. The configuration below comes from the maintainer’s example; adapt its paths and account values to your environment.
The example declares APPLYRA_API_KEY. Secret-looking values have been replaced with placeholders. Required and optional labels are shown only when the documentation states them.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| list_applications | List tracked apps with store metadata, ratings, keyword count and ASO Health scores |
| add_application | Track a new application by its store bundle ID. Fetches store metadata and computes the initial visibility score |
| list_keywords | Tracked keywords with current rank, favorite flag, difficulty/traffic scores |
| track_keywords | Track up to 20 new keywords for an application in a single call |
| untrack_keyword | Stop tracking a keyword for an application (soft delete) |
| set_keyword_favorite | Mark or unmark a tracked keyword as favorite for a specific app |
| inspect_keyword | Deep-analyze any keyword: difficulty, traffic, KEI, top 20 apps, related keywords |
| list_keyword_inspections | Past keyword inspections with their scores |
| run_autocomplete | Fetch autocomplete suggestions from the App Store or Google Play |
| list_autocomplete_history | Past autocomplete queries |
| run_niche_analysis | Cluster a niche topic into sub-niches with opportunity scores |
| list_niche_analyses | Past niche analyses |
| top_charts | Top apps chart for a store/country/category/collection, with daily rank movement |
| list_top_chart_categories | Categories and collections supported by top_charts, per store |
| get_keyword_rank_history | Daily rank evolution over a date range |
| get_app_score_history | Daily visibility score history for an app |
| get_aso_health | Full listing audit for an app: coverage, targeting and appeal, every field, and what to fix |
| check_metadata | Check draft listing text against each store's limits and forbidden copy. Instant, no store lookup |
| simulate_metadata | Score a listing that does not exist yet and see the gain against the app's current score |
| list_metadata_simulations | Listing drafts already scored on the account (titles and scores) |
| get_metadata_simulation | One saved draft in full: its four fields, its context and its findings |
| list_competitors | Competitor pairs with side-by-side visibility scores |
| add_competitor | Add a competitor app to one of your applications by its store bundle ID |
| remove_competitor | Remove a competitor relationship by its internal ID |
| get_account_usage | Current usage vs. plan limits |
{
"mcpServers": {
"applyra": {
"command": "npx",
"args": [
"-y",
"@applyra/mcp-server"
],
"env": {
"APPLYRA_API_KEY": "YOUR_APPLYRA_API_KEY"
}
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
| Variable | Description | Required |
|---|---|---|
| APPLYRA_API_KEY | Declared in the maintainer’s client configuration. | Check documentation |
Read, search and edit files inside allowed directories with the Model Context Protocol reference Filesystem server.
Retrieve version-aware library documentation and code examples with Context7 MCP, using resolve-library-id and query-docs.
基于 FastMCP 的 Model Context Protocol (MCP) 服务器，提供 OSIM (Open Security Information Model) 数据标准 schema 的查询和访问能力。
MCP Server for interacting with Salesforce instances
Taroify MCP 是一项独立的 MCP（模型上下文协议）服务，旨在将 Taroify 与大模型连接起来。它使大模型能够直接从文档中检索组件、API数据。
kintone と連携するためのMCP (Model Context Protocol) サーバーのサンプル実装です。 このサーバーは、AI アシスタント（Claude等）が kintone のデータを読み取り、操作できるようにします。