MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
제작자가 쓴 설명(영어 원문)
Context hygiene for Claude Code: drift detection, re-read dedup, and token analytics.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"sipcode": {
"command": "npx",
"args": [
"-y",
"sipcode",
"sipcode-mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add sipcode -- npx -y sipcode sipcode-mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"sipcode": {
"command": "npx",
"args": [
"-y",
"sipcode",
"sipcode-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"sipcode": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"sipcode",
"sipcode-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 Anuj7411 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.7.1)은 25일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Sipcode
Keep Claude Code's context clean for sharper answers and lower cost, automatically.
Website · Compare · Releases
npm i -g sipcode
sipcode init
That is it. Your next Claude Code session will use Sipcode automatically. Verify a few minutes later:
sipcode drift
If the output reads no drift, context health stable, Sipcode is doing its job.
Already installed? Keep it fresh. Sipcode makes zero network calls, so it can't pop an "update available" notice. Build a weekly habit: run
sipcode update(ornpm i -g sipcode@latest) to pull the latest fixes. Full details in Updating Sipcode.
Sipcode is a free command-line tool that sits between you and Claude Code. It does three things:
It is open source under the MIT license. It makes zero network calls during normal use. Your data never leaves your laptop.
| Sipcode | Tool A | Tool B | Tool C | |
|---|---|---|---|---|
| Approach | Live PreToolUse hook | Cross-session memory store | Static methodology | RAG retrieval server |
| Caps verbose tool output | ✓ | ✗ | docs only | ✗ |
| Dedups same-session re-reads | ✓ | ✗ | docs only | ✗ |
| Mid-session install support | ✓ Verified Warm-Fill | n/a | n/a | n/a |
| Zero false-dedup by construction | ✓ | n/a | n/a | n/a |
| Reproducible benchmark on locked corpus | ✓ 62.6% median (20 synthetic tasks) | ✗ | ✗ | ✗ |
| Self-introspection MCP tools | ✓ 16 tools | ✗ | ✗ | partial |
| Agents covered | Claude Code (all features); OpenAI Codex (spend analytics and usage limits, no hook) | not compared | not compared | not compared |
| Zero network calls in normal use | ✓ | ✓ | n/a | ✗ |
| MIT licensed | ✓ | ✓ | ✓ | ✓ |
Sipcode is complementary to memory tools that persist context across sessions (Tool A in the table). Sipcode keeps each individual session clean. They solve different problems. Run both for maximum effect.
Full feature-by-feature comparison with tool names revealed: anuj7411.github.io/sipcode/compare
If you use Claude Code for real work, you have already felt this:
Sipcode measures the bloat, then removes the parts Claude does not need. Run sipcode benchmark on any machine and you will see the same 62.6% median reduction on the locked 20-task corpus. That corpus is synthetic: scripted pairs of Claude Code transcripts (without and with Sipcode), not recordings of live sessions. It shows what Sipcode's mechanisms remove from a modeled session. Your own number depends on your workload, and sipcode impact measures it on your real sessions.
After installing, here are the five commands that show you what Sipcode is doing.
sipcode driftTells you if your current Claude Code session is drifting from your normal usage pattern. Bloated context, repeated reads, stale signals are all flagged here.
✓ Sipcode drift: no drift, context health stable vs your recent baseline.
By default it checks your most recent session, across Claude Code and Codex. --session checks a specific one, --here limits it to sessions from the folder you are in, and --agent claude-code or --agent codex picks the tool.
sipcode proxy --statsShows what Sipcode caught in the current session, broken down by rewriter.
Sipcode proxy, rewrite stats
total rewrites: 144 est. tokens saved: ~288,685 (heuristic) signal kept: 67% (med), weighted across all rewrites
sipcode benchmarkRuns the locked 20-task corpus and produces a reproducible savings number. Anyone, anywhere can run this and get 62.6%. The transcripts are scripted, not recorded from live sessions, so read it as a model of Sipcode's mechanisms rather than a measured bill (see METHODOLOGY).
62.6% median savings on a locked 20-task corpus
range 37.4% to 80.6% 3,567,170 tokens $22.48
sipcode todayDaily spend summary. Tokens used, sessions, output ratio, comparison to your 30-day median.
spend so far $1.20 across 4 sessions
tokens so far 943.8K output ratio 3.7%
sipcode forecastMonth-end projection based on your last 14 days.
projected month-end $17,674 (range $14,139 to $21,208)
Sipcode also reads OpenAI Codex CLI session logs (~/.codex/sessions and ~/.codex/archived_sessions, or the folder CODEX_HOME points to). For Codex this is spend analytics and usage limits: Sipcode reports what your Codex sessions used, where the tokens went, and how close you are to your plan's limits. It does not change what Codex does.
Commands that read Codex: stats, today, forecast, trend, impact, why, receipt, drift, regress and limits (Codex only), plus the session tools in the MCP server (they take an optional agent input: "claude-code" or "codex") and get_codex_limits.
--agent codex shows Codex only. --agent claude-code shows Claude Code only.--agent flag and both tools installed, stats, today, forecast, trend and impact print one section per tool. stats, today and forecast end with one combined line, in this shape: Both tools: <total tokens> tokens · ~$<Claude Code> + ~$<Codex>
why, receipt and drift report on the most recent session across both tools. When the other tool has a recent session too, a one-line hint names it and the flag that shows it.--here works for Codex too: it matches the working folder Codex recorded for each session.--json covers one tool per call. Without --agent it covers Claude Code and prints a note on stderr when Codex logs exist too. Add --agent codex for Codex JSON.--agent flag on a machine with Cursor and Codex, Sipcode shows Codex (it does not read Cursor's session logs).How Codex tokens are counted. Sipcode reads Codex's per-request usage records, or, in logs from older Codex versions, the change in the running total Codex logs after each request. Cached input is part of Codex's input count, so Sipcode never bills cached tokens twice. A request copied into a resumed or forked session file is counted once. On the maintainer's machine, Sipcode's per-file totals equal Codex's own final total_token_usage on all 15 real session logs, and an independent counter that shares no code with Sipcode (scripts/verify-counts.mjs) cross-checks every period command against the same logs.
Prices. Codex models are priced from OpenAI's API price table (developers.openai.com/api/docs/pricing, and each Codex model's page under developers.openai.com/api/docs/models, as of 2026-10-09), including the long-context rate for prompts over 272,000 input tokens. A model with no known price is shown as unpriced: its tokens are still counted, a line under the cost says how many were left out of it, and it is never shown as $0.
Not supported for Codex yet: writing rules to AGENTS.md (rules, and the rules step of init), registering the MCP server in Codex, the proxy and hooks (proxy, hygiene), estimate and benchmark. rules --agent codex and estimate --agent codex stop with error E009 instead of showing Claude Code data.
Compressed Codex logs. Codex compresses older session logs to .jsonl.zst. Sipcode reads them exactly like plain logs on Node.js 22.15 or newer. On an older Node.js it skips them, and every report starts with a warning that says how many it could not read and that reading them needs Node.js 22.15 or newer. A damaged or unreadable log gets the same kind of warning. With --json the warning is a note on stderr and the JSON is unchanged.
sipcode limitsCodex writes your plan's usage-limit readings into its own logs after each request. sipcode limits reads them, with zero network calls, and answers three questions: when will I hit my limit, what used it, and did it shrink.
Example output of sipcode limits --since all (the tokens-per-1% history here goes back further than the default 90 days):
sipcode limits · Codex · plan: go · as of 2h ago (your last Codex request)
Weekly limit 62% used resets Wed 14 Oct 14:00 at this pace: runs out Tue 13 Oct ~18:00 30-day limit 22% used resets Mon 2 Nov at this pace: lasts until reset
What used your weekly limit (since Wed 7 Oct) 0199a1b2-c3d4-7a11 sipcode 31% 3.1M tokens 0199a0f7-11aa-7b02 my-app 17% 1.4M tokens codex-auto-review (9 requests) 6% unattributed (no Codex requests on this computer) 8%
Tokens per 1% of your weekly limit (gpt-5.4) Mar 28: 425K Apr 1: 357K Apr 13: 77K Possible limit cut around Apr 13: 5.1x fewer tokens per 1%. Limits cover your whole account. Codex use on other devices or in the cloud is not in these logs and can look like a cut.
unattributed, because limits are shared with your other devices and Codex cloud.앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요