原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

yt

作者:ArasanDev版本 0.1.1i★ –i在你的电脑上运行
注册名称io.github.ArasanDev/yt

安装

概览

作者提供的说明(英文原文)

YouTube transcripts, transcript search, and channel monitoring for agents.

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 营销与社交媒体

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

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 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "yt": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/arasandev/yt:0.1.1",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add yt -- docker run -i --rm ghcr.io/arasandev/yt:0.1.1 mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "yt": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/arasandev/yt:0.1.1",
        "mcp"
      ]
    }
  }
}

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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "yt": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/arasandev/yt:0.1.1",
        "mcp"
      ]
    }
  }
}

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。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

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。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 ArasanDev 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“营销与社交媒体”中的其他服务器比较i

  • 星标数多于此分类中其他 2984 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2984 个服务器的 82% 更新
  • 基础检查结果等于或优于此分类中其他 2984 个服务器的 100%

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。

常见问题

yt 安全吗?

它在 1 项适用的基础检查中通过了 1 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。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.1)于7天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。

有什么可以替代它?

同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

替代选择

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

MCP YouTube Transcript

作者:jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT10天前更新
安装

Google Analytics MCP

作者:surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

在你的电脑上运行★ 244MIT10天前更新
安装

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

在云端运行★ 137MIT10天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

yt

YouTube transcripts for agents and humans. One static Go binary, no API key, no AI dependencies, no runtime requirements.

  • Fetches a video's own caption tracks (manual or auto-generated) via YouTube's internal Innertube API, using ANDROID/IOS client contexts — the WEB-client caption URLs have been pot-token gated since mid-2025 and return empty bodies.
  • Cascades innertube-android → innertube-ios → watch-page so a single throttled endpoint doesn't take the fetch down; every response reports which method won (source).
  • Channel monitoring: yt channel @handle (or list_channel_videos) resolves a handle and lists the latest uploads with exact publish timestamps from the channel RSS feed, so an agent can diff against a watermark and see what is new.
  • Same binary is the MCP server: yt mcp, or bare yt when stdin is piped (the shape MCP clients spawn). Bare yt at a terminal prints help.
  • MCP responses are designed for agent context budgets: bounded payloads, structural truncation with exact resume pointers, time/cue-addressed ranges, server-side search, typed errors, and session-level caching so one get_video_info + get_transcript + search_transcript share a single player fetch.

Dependencies: cobra (CLI), modelcontextprotocol/go-sdk (official MCP SDK), and golang.org/x/term (TTY detection). The YouTube fetch layer is stdlib only — net/http, encoding/json, encoding/xml.

Layout

The repository root is the Go module (github.com/ArasanDev/yt) and the product root.

cmd/yt/               binary entry point

internal/cli/ cobra commands and flags internal/mcp/ MCP tool schemas, handlers, safety warnings internal/youtube/ Innertube client, captions, channels, cache, typed failures internal/search/ pure transcript search internal/render/ block/cue rendering, SRT, truncation metadata internal/transcript/ shared Segment/Transcript model and timestamp helpers internal/apperr/ typed error contract (code, retryable, suggestion) internal/version/ build version, commit, and date

CI lives in .github/workflows/ci.yml and runs gofmt, go vet, go test -race, a native build, and a cross-build matrix for the release targets.

Dependencies point inward: cli and mcp depend on youtube, search, render, and transcript; youtube depends on apperr and transcript; search and render depend only on transcript. The acquisition layer does not import the adapters.

Install

Homebrew (macOS/Linux)
brew trust arasandev/tap          # Homebrew 7+ trusts third-party taps explicitly

brew install --cask arasandev/tap/yt

Install script (macOS/Linux)
curl -fsSL https://raw.githubusercontent.com/ArasanDev/yt/main/install.sh | sh

The script downloads the latest release for your OS/architecture, verifies it against checksums.txt, and installs to /usr/local/bin when writable, otherwise ~/.local/bin. Override the target with YT_INSTALL_DIR and pin a version with YT_VERSION:

YT_VERSION=v0.1.0 YT_INSTALL_DIR="$HOME/bin" \

curl -fsSL https://raw.githubusercontent.com/ArasanDev/yt/main/install.sh | sh

Go developers
go install github.com/ArasanDev/yt/cmd/yt@latest

go install records the module version, so yt --version reports the release even though ldflags cannot be injected. Use make install for a local build that also stamps commit and date.

Docker
docker run --rm -i ghcr.io/arasandev/yt:latest mcp

CLI use:

docker run --rm ghcr.io/arasandev/yt:latest transcript dQw4w9WgXcQ

The image is a distroless static build. With no TTY, bare yt already serves MCP, so the default container command is mcp.

Linux packages

Release assets include .deb, .rpm, and .apk packages for amd64 and arm64:

sudo dpkg -i yt_<version>_linux_amd64.deb

sudo rpm -i yt_ _linux_amd64.rpm sudo apk add --allow-untrusted yt_ _linux_amd64.apk

Prebuilt binaries

Every release publishes archives, Linux packages, and a checksums.txt:

https://github.com/ArasanDev/yt/releases

Targets: darwin/linux/windows on amd64 and arm64; Linux also ships deb/rpm/apk packages.

From source
git clone https://github.com/ArasanDev/yt.git

cd yt make build # ./bin/yt make install # into GOBIN with version/commit/date stamped

Release builds stamp a version, commit, and date (the default is dev):

go build -trimpath -ldflags "\

-X github.com/ArasanDev/yt/internal/version.Version=v0.1.0 \ -X github.com/ArasanDev/yt/internal/version.Commit=$(git rev-parse --short HEAD) \ -X github.com/ArasanDev/yt/internal/version.Date=$(date -u +%Y-%m-%dT%H:%M:%SZ)" \ -o bin/yt ./cmd/yt yt --version

CLI

yt transcript <url-or-id>                       # transcript to stdout

yt transcript -l en,es -t # language fallback + [MM:SS] stamps yt transcript --start 1274 --end 1290 # time range yt transcript -f srt -o subs.srt # SRT file yt transcript -f json --max-chars 2000 # cue JSON, bounded yt transcript --bare # body only, no metadata header yt transcript --start-cue 120 --max-cues 40 # resumable cue window yt search "harness engineering" # timestamped hits, no full read yt search "M C P" --match-mode any # spelled acronyms collapse to mcp yt search "state of the art" --match-mode phrase yt search "harness" --context-cues 2 # human output shows context yt tracks # list caption languages yt info # title, channel, duration, views, chapters yt channel @aiDotEngineer --limit 10 # latest uploads (exact timestamps) yt channel @aiDotEngineer --since 2026-10-01 --json yt doctor # probe which acquisition clients work yt --version # build version (or module version under go install)

Accepts watch?v=, youtu.be/, /shorts/, /live/, /embed/ URLs or a bare 11-char video ID. By default, -f text includes a metadata header and, when needed, a truncation trailer. Use --bare for body-only stdout; truncation is then reported on stderr. Fetch/renderer notes always go to stderr.

CLI usage errors and upstream failures are typed. cmd/yt prints code, retryable, retry_after_seconds, and suggestion to stderr while keeping stdout clean. Invalid formats, negative limits, and inverted time ranges fail before any network request.

MCP

yt mcp serves stdio JSON-RPC; so does bare yt when stdin is not a terminal (how MCP clients spawn a server), while bare yt at a prompt prints help. Call get_video_info first: it reports caption availability, live status, and an estimated transcript size, so you can decide between reading the whole transcript, searching it, or reading a range.

ToolPurpose
list_channel_videosLatest uploads for a channel (@handle/URL/UC…), from RSS: exact publish times, titles, links, description excerpts.
get_video_infoMetadata + caption summary + transcript size estimate + chapters. No transcript download.
get_transcriptTranscript text or cue JSON, bounded and addressable.
search_transcriptFind a topic with timestamps and context; match_mode all/any/phrase; zero results explain themselves.
list_tracksCaption tracks. Deprecated — use get_video_info.captions.

For monitoring, call list_channel_videos and pass the previous response's newest_published as since. Filtering is strictly published > since, so no video is reported twice. The feed exposes at most 15 entries and has no duration or view counts; those need get_video_info on a specific video.

Key get_transcript parameters: languages (CSV, default en; original for the uploader's own language), allow_translation, format (text|json), granularity (block default |cue), timestamp_mode (block default |cue|none), start_seconds/end_seconds, start_cue/max_cues, max_chars (default 50000; bounds the transcript body only).

Truncation is never silent: the header carries TRUNCATED next_start_seconds=… next_cue_index=…, structured metadata carries the same fields, and next_* values are exact (not rounded), so resuming at them never drops the boundary cue. max_cues clipping is reported even when end_seconds is also set. Errors come back as isError results with a machine-readable error.code (bot_check, rate_limited, no_captions, bad_request, …) plus retryable and a suggestion.

The transcript body is returned in both content and structuredContent for client compatibility, so a response is roughly twice the body size; returned_chars measures one copy.

Auto-dubbed videos list one auto-generated track per language. A track whose language differs from the uploader's known original is reported as translated=true, whether it is manual or ASR, so machine-translated speech is never presented as the speaker's words. get_video_info.captions.original_language names that track. If the player response carries no audio-track metadata and multiple caption languages exist, the original is unknown: languages=original returns an actionable no_matching_language error instead of guessing, and original_language may be empty. Request a specific language in that case.

Wire into any agent:

devin mcp add yt -- yt mcp          # Devin CLI

claude mcp add yt -- yt mcp # Claude Code

or raw mcpServers JSON (Devin, Claude Desktop, Cursor, Windsurf, …):

{"mcpServers": {"yt": {"command": "yt", "args": ["mcp"]}}}

Releasing and distribution

A v* tag triggers .github/workflows/release.yml, which:

  1. runs the test suite and GoReleaser (archives, Linux packages, checksums, GitHub Release);
  2. builds and pushes a multi-arch ghcr.io/arasandev/yt image;
  3. stamps the version into server.json and publishes to the MCP registry.
git tag v0.1.0

git push origin v0.1.0

Homebrew cask updates are skipped unless the repository has a HOMEBREW_TAP_GITHUB_TOKEN secret: a fine-grained PAT with contents: write on ArasanDev/homebrew-tap. Without it, the release still ships binaries, Docker, and MCP metadata; add the cask manually or add the secret and re-run.

The MCP registry job is best-effort (continue-on-error). GHCR packages are private by default: set the yt package to public once in the package settings, then re-run the job. The registry checks the image annotation io.modelcontextprotocol.server.name against server.json's name, so those two strings must stay in sync.

Useful local checks before tagging:

goreleaser check

goreleaser release --snapshot --clean # artifacts in dist/, never published docker build --build-arg VERSION=dev -t yt:dev .

Development

make build          # ./bin/yt

make test # go test -race ./... make check # gofmt + go vet + go test -race make snapshot # local GoReleaser snapshot make clean

See AGENTS.md for the architecture, contracts, and conventions agents must preserve. In short: stdout is data, stderr is diagnostics; errors are typed; truncation is never silent and resume pointers are exact; provenance and content_trust labels are not optional; tests never hit the network.

Caveats

  • IP blocking: datacenter IPs (AWS/GCP/VPS) get blocked o

只显示了开头部分;其余内容请在仓库中阅读

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