canonical: https://jentic.com/apis/appmanai.com/appmanai # appmanai Public API The appmanai Public API returns App Store and Google Play data for app store optimization work. It reads current and historical app metrics such as ratings, installs, and metadata, lists app reviews and category rankings, and reports keyword metrics including search volume, difficulty, and how an app ranks for a term over time. Two generate endpoints produce keyword and app-metadata suggestions, and reference endpoints list the supported countries, categories, and features. ## For AI agents Read App Store and Google Play data for ASO: app metadata, ratings and install history, reviews, category rankings, and keyword metrics and suggestions. Reads are GET with a bearer key; the two generate endpoints are POST. ## Scope Does not submit apps, manage store listings, or run ad campaigns. Use for reading App Store and Google Play metrics and keyword data only. ## Capabilities - Search the App Store and Google Play for apps by name - Read current and historical app metrics for ratings, installs, and metadata - Pull app reviews and category rankings for an app - Look up keyword metrics such as search volume, difficulty, and ranking - Track how an app ranks for a keyword over time and worldwide - Find keyword suggestions, competitors, and keyword overlap for an app - Generate keyword and app-metadata suggestions from the generate endpoints ## Use cases ### App Store Optimization Research An agent researches a target keyword by reading its search volume and difficulty, then checks how a given app ranks for it across markets. appmanai returns keyword metrics and per-app rankings so the agent can decide which terms are worth optimizing without pulling data from several tools. Example prompt: Call GET `/keywords/metrics` for a term, then GET `/keywords/app/metrics/rankings` to read how the app ranks for it ### Competitor and Review Monitoring A monitoring workflow pulls an app's ratings history, recent reviews, and category rankings on a schedule to track how it performs against competitors. The agent reads review and ranking data per app so changes in sentiment or position surface without manual store checks. Example prompt: Call GET `/apps/reviews` for an app, then GET `/apps/metrics/ratings/history` to chart its rating trend ### AI Agent Integration via Jentic An AI agent reaches the appmanai Public API through Jentic without holding the bearer key itself. It searches by intent, receives the matching operation with its input schema, and executes the call with the credential injected at run time, so app and keyword data flow into a larger ASO workflow. Example prompt: Search Jentic for 'read app store keyword metrics', load the GET `/keywords/metrics` schema, and execute it with Jentic-managed credentials ## Key endpoints | Method | Path | Description | | --- | --- | --- | | GET | `/apps/search` | Search apps by name | | GET | `/apps/metrics/metadata` | Read current app metadata | | GET | `/apps/metrics/ratings/history` | Read ratings history | | GET | `/apps/reviews` | List app reviews | | GET | `/keywords/metrics` | Read current keyword metrics | | GET | `/keywords/app/metrics/rankings` | Read keyword rankings for an app | | GET | `/categories/top-apps` | Read current top charts for a category | | POST | `/generate/keywords` | Generate keyword suggestions | ## Key resources - **Apps** — Search apps and read metadata, metrics, reviews, and rankings via `/apps/search`, `/apps/metrics/metadata`, and `/apps/reviews` - **Keywords** — Read keyword metrics, rankings, and suggestions via `/keywords/metrics` and `/keywords/app/metrics/rankings` - **Generation and Reference** — Generate keyword and metadata suggestions and list supported countries and categories via `/generate/keywords` and `/resources/countries` ## AI readiness This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use. - **Score:** 68 / 100 - **Maturity:** AI-Aware - **Dimensions:** - Foundational Compliance: 99 / 100 - Developer Experience & Jentic Compatibility: 69 / 100 - AI-Readiness & Agent Experience: 51 / 100 - Agent Usability: 94 / 100 - Security: 60 / 100 - AI Discoverability: 64 / 100 - **View full report:** https://jentic.com/apis/appmanai.com/appmanai/scorecard - **How the score is calculated:** https://docs.jentic.com/reference/api-readiness-framework/overview/ - **More about the dimensions:** https://docs.jentic.com/reference/api-readiness-framework/specification/#dimensional-model-overview ### Score it yourself Every API in the directory is allowlisted, so you can re-score it with no key required. - **Score your own API:** https://jentic.com/scorecard.md - **Scoring CLI agent skill:** https://github.com/jentic/jentic-api-scorecard/blob/main/skills/jentic-api-scorecard/SKILL.md ```sh npx @jentic/api-scorecard-cli score ``` ## Why Jentic - **Setup:** Wiring the appmanai Public API by hand means managing its bearer key and juggling the current, history, and worldwide variants of each metric endpoint yourself. Through Jentic you install once, import appmanai from the API Directory, store the key once, and your agent calls it. - **Permission scoping:** appmanai carries the app and keyword identifiers inside each request, so a rule bounds which operations your agent may call rather than which app it reads. You choose the operations it may use, such as the keyword and ranking reads, so the generate operations are not included unless you add them. - **Credential handling:** Your appmanai key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context. - **Discovery method:** Agents search Jentic by intent such as 'read app store keyword metrics' or 'list app reviews', and Jentic returns the matching appmanai operation with its input schema so the agent calls the right endpoint without browsing the reference docs. ## Related APIs - **AppSkyline** — App store optimization data for keywords, apps, and rank tracking - **Semrush** — Web search keyword research and competitive SEO data - **Ahrefs** — Backlink and keyword data for web SEO ## FAQ ### What authentication does the appmanai Public API use? The appmanai Public API authenticates with a bearer key in the Authorization header, per its OpenAPI spec. Read endpoints are GET with query parameters and the two generate endpoints are POST with a JSON body. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at execution time, so it never reaches the agent. ### Can I read an app's keyword rankings with the appmanai Public API? Yes. GET `/keywords/metrics` returns a term's search volume and difficulty, and GET `/keywords/app/metrics/rankings` returns how a given app ranks for it, with worldwide and history variants for broader coverage. The responses are structured JSON an agent can parse directly. ### What are the rate limits for the appmanai Public API? The appmanai OpenAPI spec does not specify rate limits. Watch for HTTP 429 responses and check appmanai's documentation for the current limits before pulling large batches of app or keyword data. ### How do I read app store keyword metrics with the appmanai Public API through Jentic? Search Jentic for 'read app store keyword metrics', and it returns the appmanai operation with its input schema. Load the schema and execute GET `/keywords/metrics` with the credential injected at run time. To run it on your own infrastructure, install Jentic One from its GitHub repo. ### Is there an appmanai MCP server? You don't need an MCP server to give your agent the appmanai Public API. Jentic connects it directly from the API Directory: import it, store your key once, and your agent calls the app and keyword operations it needs. Operations are discovered on demand, so no extra server's tool definitions sit in the agent's context. ### Can I limit what my agent is allowed to do with the appmanai Public API? Yes. appmanai carries the app and keyword identifiers inside each request, so a rule bounds which operations your agent may call. Allow only the read lookups the task needs, such as keyword metrics and rankings, so the generate operations stay off the table, and every call runs through your own instance where it is logged.