
AsoBeast
com.asobeastv1.8.0更新于 Oct 6, 2026
App Store and Google Play ASO: keyword rankings, competitors, reviews, audits and an action queue.
概览
让助手通过 23 个只读工具查询自建或托管的 AsoBeast 实例,获取 App Store 与 Google Play 的 ASO 数据。
- 功能
- AsoBeast 是一款面向 Apple App Store 和 Google Play 的应用商店优化(ASO)工具与关键词排名跟踪器。其 MCP 服务器通过 stdio 或远程端点提供 23 个只读工具,助手可据此查询关键词排名、竞争对手、评论、审计结果和按优先级排序的行动队列。所有工具均为 GET 请求,并需要个人 API 令牌。
- 适用场景
- 当你已经自建或订阅 AsoBeast,并希望助手直接读取你的 ASO 数据时使用,例如查看关键词排名、比较竞争对手、查看审计发现或获取行动队列。
- 运行要求
- 需要一个正在运行的 AsoBeast 实例,可自建(Docker 与 Compose,约 2 GB 内存和 5 GB 磁盘)或使用托管服务。需要个人只读 AsoBeast API 令牌,通过 Authorization bearer 请求头发送。无需商店凭据或第三方 API 密钥。
安装
在 SourceWeft 中
- 打开 控制台中的 AsoBeast,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
其他 MCP 客户端
把它添加到你客户端的 mcpServers 配置中。
{
"mcpServers": {
"asobeast": {
"type": "http",
"url": "https://app.asobeast.com/api/backend/mcp"
}
}
}README
AsoBeast
AsoBeast is an App Store Optimization (ASO) tool and keyword rank tracker for the Apple App Store and Google Play.
Use the hosted service at asobeast.com, or self-host the open source edition on your own server.
[License: AGPL-3.0] [Release] [Documentation] [Stores]
Website · Quickstart · Self-host · MCP server · API · Changelog
What is AsoBeast?
AsoBeast is an App Store Optimization (ASO) tool and keyword rank tracker for the Apple App Store and Google Play. It imports a listing, tracks keyword rankings daily to a depth of 200, watches competitors, reviews and metadata, and turns that history into a prioritized queue of ASO work. This repository is the free, open source edition that you run on your own server, and the hosted service at asobeast.com runs the same code.
Every store request runs on the machine hosting AsoBeast as an ordinary public search or page request, so Apple and Google see each tracked phrase the way they see any search. There is no ASO vendor to sign up with, no API key to buy, and no ASO vendor that learns which keywords you target. Beyond those store requests, your data stays in your deployment unless you explicitly enable an outbound integration such as webhook alerts, email, OpenAI assistance, Apple Ads search popularity or store status updates.
Why AsoBeast?
- No accounts, no vendor API keys. AsoBeast collects from the public store endpoints at a deliberately modest rate. You need Docker and nothing else.
- Your keyword list is your strategy. It lives in your database and is never sent to an ASO vendor, so no competitor intelligence product is quietly assembling it. The stores only ever see one search at a time.
- Both stores as one tracking entity. One app row tracks keywords across many storefronts, so
usanddeare markets on the same listing rather than two subscriptions. - Every score shows its evidence. Popularity and difficulty carry their source, calculation version, capture date and confidence, so you can argue with a number instead of trusting it.
- Deterministic recommendations. Fifteen rules turn stored history into an explainable work queue. AI is optional garnish that can summarize an action, never invent or reorder one.
- AGPL-3.0, no open core. Every feature the hosted service runs is in this repository.
Features
A guide for each of these lives in the documentation.
Quick start
You need Docker with Compose, roughly 2 GB of memory and 5 GB of disk.
Open http://localhost:3001 and create the owner account. Registration closes automatically once it exists. Safari does not keep the session cookie over plain HTTP, so use Chrome or Firefox for a local evaluation, or see signing in returns to the sign in form. Import a store URL and keyword tracking starts immediately.
Prefer published images to a build? docker-compose.pull.yml runs the same stack from GHCR without a clone:
Full walkthrough: quickstart. Image tags, pinning and upgrades: run a published release.
How AsoBeast compares
A hosted AsoBeast is a separate product built from this same repository. Self-hosted installations get every feature.
Tech stack
pnpm and Turborepo, TypeScript strict throughout, NestJS, Prisma, PostgreSQL 18, BullMQ, Redis 8, Next.js with Tailwind, Docker Compose.
Contributor setup, architecture and the module map: local development and how AsoBeast works.
Configuration
Every environment variable, with defaults and what each one changes, is documented in the configuration reference. apps/api/.env.example and apps/web/.env.example are the authoritative lists in the repository.
A default installation needs two variables, POSTGRES_PASSWORD and AUTH_SECRET. Everything else has a working default.
FAQ
What is App Store Optimization?
App Store Optimization is the practice of improving how an app ranks and converts in App Store and Google Play search. It covers keyword targeting in indexed metadata fields, competitor positioning, ratings and reviews, and category performance.
Does AsoBeast need an App Store Connect or Google Play Console account?
No. AsoBeast reads public store data, so you can track any app including your competitors. It never asks for store credentials or an ASO vendor API key.
Which app stores does AsoBeast support?
Both the Apple App Store and Google Play. Apple indexes a title, a subtitle and a private 100 byte keyword field. Google Play indexes a title, an 80 character short description and a long description, so subtitle and keyword field stay Apple only concepts. See stores.
How often does it check rankings?
Once a day by default, on a UTC cron you control. Rank checks capture position to a depth of 200, and a position of null means checked and not found within that depth rather than zero. See positions.
Can I track more than one country?
Yes. An app is imported once, and keyword tracking carries its own storefront, so one listing can track keywords in many markets at once. Each added market multiplies daily store requests, and the settings page shows a budget card that estimates the fan-out. See countries and markets.
Is any of my data sent anywhere?
Only the store requests themselves, which send each tracked phrase to the App Store or Google Play as an ordinary search, from your own address or through a proxy provider if you configure one. Beyond those, webhook alerts, SMTP email, OpenAI assistance, Apple Ads search popularity and the store status poll are the only outbound integrations, and each is off until configured. There is no telemetry. See what leaves your deployment.
Can I connect AsoBeast to Claude or another AI agent?
Yes. AsoBeast ships a Model Context Protocol server with 23 read-only tools, available as a local stdio process or as a remote endpoint on your instance. Every tool is a GET and requires a personal API token. See MCP.
Is AsoBeast really free?
The software is, entirely. It is AGPL-3.0 with no open core and no feature held back for a commercial edition, so a self-hosted installation has everything. A hosted service built from this same repository is charged for the hosting it uses, never for features. If you run a modified version as a network service, the AGPL asks you to offer that modified source to its users.
Documentation
Limitations
Worth knowing before you rely on it:
- Scores are store-specific estimates. Popularity and difficulty come from different public evidence on each store, so the numbers are not comparable across stores and are not a substitute for first-party acquisition data.
- Scrapers can break. AsoBeast reads public endpoints. When a store changes one, a parser can fail. Failures fail the job, which BullMQ retries with backoff, and never take down request handling.
- Store rate limits bind first, not hardware. The public endpoints tolerate only modest request rates per address, which is what caps how many keyword markets one instance can track. See capacity and limits.
- Operations are yours. Backups, TLS, secret rotation, monitoring and upgrades are the operator's responsibility. Verify a restore before you rely on a backup.
Roadmap
The 1.x line is current, and the changelog names the latest release. What remains open:
- A per-user permission model finer than owner and member, and one account in several workspaces.
- Better popularity calibration using licensed or first-party acquisition data.
- A per-market app detail switcher, so snapshots, reviews and category ranks are not limited to the home storefront.
- Write capable MCP tools, behind an explicit opt-in. Every tool is read-only today on purpose.
Release policy and the 1.x compatibility promise: upgrade and roll back.
Contributing
Pull requests are welcome. Read CONTRIBUTING.md first for the commit conventions, the compatibility promise and how the test suites are run. Security reports go through SECURITY.md, never a public issue.
License
This repository's source code is available under the AGPL-3.0 license.
来源:README.md,提交 11e489a
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0版本历史
1- v1.8.0最新Oct 6, 2026

