MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
作者提供的说明(英文原文)
ASO for your AI: keywords, rankings, competitors and ads across 2.5M+ App Store apps.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
Authorization你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http asonix https://api.asonix.io/mcp --header 'Authorization: Bearer {token}'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"asonix": {
"url": "https://api.asonix.io/mcp",
"headers": {
"Authorization": "Bearer {token}"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"asonix": {
"type": "http",
"url": "https://api.asonix.io/mcp",
"headers": {
"Authorization": "Bearer {token}"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 必填 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
工具名称和描述与服务器在 2026年11月6日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。
get_ai_visibility_overviewRead a tracked app's stored AI recommendation benchmark: coverage, mention/recommendation/App Store citation rates, weekly history and topic/prompt summaries with run IDs. Not ASO visibility. No collection or model calls. Defaults to four weeks; no benchmark returns NOT_STARTED.
get_ai_visibility_reasonsRead cached recommendation themes, exact answer quotes and description passage matches. Includes analysis status, timestamps and its own evidence denominator (which can differ from the overview). No generation or refresh. Full descriptions stay in get_app_overview; this returns m
get_ai_visibility_evidenceRead a saved AI Visibility answer by runId, or recent answers for one promptId (exactly one required). Defaults to one run; use nextBefore for older prompt runs. Citations, resolved mentions and classification coverage are included. includeTrace adds captured searches; their sour
add_appAdd an App Store app to the current Asonix workspace by App Store ID or app name/search query.
create_unreleased_appCreate a private unreleased app idea in the current Asonix workspace. Use this when the user's app is not on the App Store yet; then add researched keywords with add_keywords.
search_appsFind App Store apps by name or developer, to get an app's appStoreId; use it before add_app when the user gives an app name. Returns at most 12 apps, in Apple's name-search order, which is not the keyword ranking: for who ranks for a keyword, use get_keyword_top_apps. Screenshot
add_keywordsAdd one or more tracked keywords to an app in the current Asonix workspace and queue ranking refresh so popularity, difficulty, opportunity, and rank evidence can be collected. For agent-researched candidates, call evaluate_keywords first and add app-relevant primary or secondary
star_keywordStar/favorite a keyword research keyword in the current workspace by keywordId or term.
unstar_keywordRemove a keyword research keyword from the current workspace favorites by keywordId or term.
list_appsList apps tracked in the current Asonix workspace: names, App Store IDs, platforms, tracked storefronts, ratings and tracked-keyword counts. Pages with limit (default 20, max 100) and offset; q filters by name, developer, genre or ID. For one app's details use get_app_overview; f
list_tracked_keywordsOne tracked app's tracked keywords with rank, popularity, difficulty, relevance and an ad summary, in one storefront or all. Use it for "how are my keywords doing". For the app's listing or ratings, or an untracked app, use get_app_overview. Paged: limit (default 30, max 100) and
get_app_meta_adsAn App Store app's Meta ads (Facebook, Instagram, Messenger, Audience Network) from Asonix's monthly Ad Library crawl, worldwide, for any app: active ads with text, call to action, start date, platforms and an Ad Library link, and past ads with their dates. status not_found is no
refresh_app_rankingsQueue a ranking refresh for one tracked app's keywords not checked in the last 18 hours, and return at once with jobIds. Omit country for every tracked storefront; one refreshed recently is listed in coolingDown. A refresh can take 10 minutes or more, so do not wait in a loop: te
get_ranking_refresh_statusReport progress of a ranking refresh started by refresh_app_rankings, or of the rankingRefreshJob id returned by add_keywords: keywords done, failed, and remaining per storefront. Poll no more often than pollAfterSeconds. When finished is true, read the full updated ranks with li
get_workspace_keyword_opportunitiesReturn top scored keyword opportunities across all tracked apps in the current Asonix workspace, including shipped and unreleased apps, all countries, and rank/popularity/difficulty/opportunity evidence. Use this for requests like analyzing all apps or finding the top 100 opportu
check_tracked_keywordsCheck candidate keyword terms against one tracked app's existing tracked keywords without dumping the full keyword table. iOS keyword rows include cached topAdvertisers; pending observations queue in the background. Use this before calling a candidate a missing gap, before add_ke
get_app_overviewAn app's overview in one storefront, for any App Store app. storeListing is the storefront's listing and rating. Lists are counts: include adds the full description, countryRatings, listingCountries or keywordSuggestions. tracked says whether the workspace tracks it; its keywords
get_app_visibility_historyReturn tracked ASO visibility score history for an app, useful for momentum and trend analysis.
get_app_rank_historyReturn rank, popularity, or difficulty history for one tracked app keyword in a storefront.
get_app_rating_historyReturn stored public rating history for any App Store app, tracked or not, with deltas: the history the Inspect dialog shows. Asonix records rating history only while some workspace tracks the app, so an app no workspace has tracked has none; for current ratings of any app, use g
get_app_chartsWhere any App Store app placed in Apple's iPhone top charts (free, paid, grossing; overall and by category) per storefront: best rank, days on chart, latest position. days: 7, 30 (default), 90 or 365. includeDailyCells adds a cell per chart per day: a number is the best position,
get_keyword_suggestions_for_appRefresh and return Asonix keyword suggestions for one tracked app and storefront. Includes suggestionRelevance rows and inline metadata-plan relevanceScore/relevanceStatus; missing scores queue in the background.
research_app_keywordsStart keyword research for a tracked app in one call: Asonix suggestions, known public rankings and market keyword opportunities, each with the app's relevance. It can refresh the suggestion list, which spends the app's daily budget. Seed searches are checked privately unless sto
extract_competitor_keywordsExtract keyword opportunities from competitor public rankings and compare them against the tracked app. Includes relevanceScore/relevanceStatus for the target app, not the competitors; missing scores queue in the background. Provide competitorAppStoreIds, or provide a seed keywor
get_localization_opportunitiesBuild and return localization and translated market keyword opportunity requests for one tracked app.
get_public_app_rankingsReturn known public App Store keyword rankings where an app appears in collected SERPs.
search_keywordsSearch Asonix keyword research summaries by query, market, platform, scores, and market estimates. iOS keyword rows include cached topAdvertisers; pending observations queue in the background, so retry this tool later.
get_keyword_relevanceApp-specific relevance (0–100) of up to 100 keywords for a tracked app, from the same scorer as the UI. Returns at once with ready, pending, failed or unavailable for each keyword. Pending is not zero: call again after 3 seconds or more, backing off. retry=true retries failed wor
evaluate_keywordsRank and classify candidate keywords by Asonix popularity, difficulty and opportunity. Use it before recommending keywords or calling add_keywords. Known keywords reuse stored scores; up to 20 new ones per call are scored privately, without adding them to public research. Pass po
get_keyword_top_appsWho ranks for a keyword in one storefront; appStoreId gives that app's rank. Uses results Asonix checked in the last 18 hours, else a private live check; saves nothing. Adds stored scores when Asonix has them; to score a new keyword, use evaluate_keywords. To find an app by name,
get_keyword_top_advertisersApps seen in native App Store search ads for one iPhone keyword in one Apple Ads country: the last 7 days' check coverage, last seen, and 30 days of history. Cached only, no live Apple request; pending collection fills in on a later call. Absence does not prove an app stopped bid
get_app_search_ads_keywordsKeywords where an iPhone app's App Store search ads were seen in the last 30 days, in all countries or one. Asonix checks each keyword about once a day, so a missing keyword may still be bid on. observedSharePercent7d is the share of the last 7 days' checks that showed the ad, no
get_keyword_historyReturn keyword popularity or difficulty history for an Asonix keyword, with cached topAdvertisers for eligible iOS keywords. Pending advertiser observations are queued; retry later.
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册中心没有列出源代码仓库,因此无法将发布者(asonix.io)与代码对应起来
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
在 142 毫秒内响应(HTTP 200)
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已读取 33 个工具描述,未发现针对 AI 的隐藏指令
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 3 项适用的基础检查中通过了 2 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于前天进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
仓库中没有找到 README