MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
제작자가 쓴 설명(영어 원문)
Test decisions on a synthetic audience: studies, site audits, copy tests and post simulations.
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.
AETHERYA_API_KEY, Authorization비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"aetherya": {
"command": "npx",
"args": [
"-y",
"@aetherya/mcp"
],
"env": {
"AETHERYA_API_KEY": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add --transport http aetherya https://mcp.aetherya.ai/mcp --header 'Authorization: your-value'claude mcp add aetherya --env AETHERYA_API_KEY=your-value -- npx -y @aetherya/mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"aetherya": {
"url": "https://mcp.aetherya.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"aetherya": {
"command": "npx",
"args": [
"-y",
"@aetherya/mcp"
],
"env": {
"AETHERYA_API_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"aetherya": {
"type": "http",
"url": "https://mcp.aetherya.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"aetherya": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@aetherya/mcp"
],
"env": {
"AETHERYA_API_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
Authorization 비밀 필수 HTTP header이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
도구 이름과 설명은 서버가 2026년 11월 7일에 알려 준 그대로예요. 우리가 아니라 제작자가 쓴 글이고, 일반 텍스트로만 보여 드려요.
aetherya_list_capabilitiesList the research methods this workspace can run — with the exact stimulus fields each one requires — plus remaining plan headroom and simulation-session balance. Call this before aetherya_run_study or aetherya_test_copy to pick a method and check cost headroom. Everything Aether
aetherya_estimateQuote how many simulation sessions a run would cost, and roughly what share of your plan it would consume, before committing to it. Free — this never starts a simulation. Use it to size an audience or shorten a study when headroom is tight.
aetherya_plan_studyGive Aetherya a decision you need to make, in plain English, and it designs the study, picks or builds the audience, prices it, and runs it — then writes a decision brief. Use this when you do not already know which research method fits; use aetherya_run_study when you do. It can
aetherya_confirm_studyRespond to a plan from aetherya_plan_study. Use action 'confirm' with accept_sessions to approve the quoted cost and start the run — this is the point at which simulation sessions are spent, so check with the user first. Use 'answer' to reply to the clarifying questions (answers
aetherya_readMyrias instant read. Reads 2-5 variants against a census-weighted synthetic population for a market, in seconds, and returns each variant's predicted action propensity, its lift over the control, and which demographic archetypes favour it. A variant can be copy (text), a live pag
aetherya_run_studyRun a Research Lab study — pricing sensitivity, message testing, concept testing, focus groups — against a synthetic audience and get a structured verdict with segment breakdowns, objections and representative reactions. Call aetherya_list_capabilities first to pick a method and
aetherya_test_copyCompare 2-5 copy variants — headlines, value propositions, ad or email copy — against a synthetic audience, and get a ranked verdict with predicted action propensity, comprehension and trust per variant, plus the objections each raises. Results are SIMULATED predicted reactions,
aetherya_audit_siteRun a behavioral simulation: a synthetic audience visits a URL and predicts where real users would hesitate, get confused, or drop off, plus messaging-clarity and UX friction findings with concrete fixes. Ideal for evaluating a freshly built or changed page and getting actionable
aetherya_test_flowSimulate people who arrive from an ad (image, video or copy), land on a page, and take one of several exits (for example book a consultation, open the plan form, or leave). Reports the exit split per arm. Pass rewrites to compare a changed ad and page copy against the original on
aetherya_ask_audienceSECONDARY TOOL. Pose a question to a SINGLE synthetic persona and get one predicted, in-character response — good for an open-ended 'would this confuse someone like this?' sounding-out. The answer is SIMULATED (one persona's predicted reaction), not a real person, and ONE persona
aetherya_simulate_postRun a post (X, LinkedIn, Instagram, Facebook) or email through a synthetic audience and get predicted engagement, sentiment and representative reactions before publishing. Starts the run and waits briefly; collect with aetherya_get_result kind 'post_simulation'. Results are SIMUL
aetherya_cancelStop a study, instant read, plan, audit or post simulation that is still running. Use it when the user changes their mind or a run was started with the wrong inputs. Finished runs are not affected.
aetherya_list_runsList the workspace's recent simulations across studies, instant reads, plans, audits and post simulations, newest first, with the kind and id to pass to aetherya_get_result or aetherya_get_brief. Use it to find earlier work instead of re-running it.
aetherya_get_resultFetch the findings of a run started by aetherya_run_study, aetherya_test_copy, aetherya_audit_site, aetherya_plan_study, aetherya_read, aetherya_simulate_post, aetherya_compare_creatives, aetherya_pretest_video or aetherya_test_flow, using the kind and id from that tool's respons
aetherya_get_audit_resultFetch the result of an audit started by aetherya_audit_site, using its job_id. Returns the full simulated behavioral findings once complete, or a 'running' status to poll again. Results are SIMULATED predicted behavior, not real users.
aetherya_get_briefTurn a finished study, audit, read or post simulation into a short decision brief: the question, a direct answer, the reasoning with supporting simulated reactions, the risks, and what to do next. This is what you hand a human — use it instead of relaying raw metrics. Reuses the
aetherya_share_resultMint a shareable URL for a completed study, audit or creative comparison so someone without an Aetherya account can read the findings. Use it after aetherya_get_brief when the user wants to send the results to a colleague or client, or post them. The link is PUBLIC to anyone who
aetherya_pretest_reportAssemble a markdown pretest report (how we worked, one section per set, what the results mean, sealed predictions appendix) from finished simulations. Deterministic unless generateFixes is true (then the model drafts fixes and a one-line summary per set, if enabled on the account
aetherya_compare_creativesCompare 2+ image creatives (thumbnails, display banners, social images) against a synthetic audience. Creates the experiment, uploads the images, attaches the audience and drafts the comparison (free). It then returns status 'needs_price_confirmation' with the quoted simulation s
aetherya_pretest_videoPretest a short video (mp4, mov, webm; max 512 MB, 10 minutes) against a synthetic audience: hook score, attention curve, drop-off points. Uploads the file (video_path on this machine, or video_url), splits it into scenes, then returns status 'needs_price_confirmation' with the q
aetherya_seal_predictionLock a prediction (a creative comparison ranking, a video analysis, a study or a manual payload) with a SHA-256 hash and timestamp, so it can later be compared with what really happened. Pass source_id to seal a finished simulation, or payload for a manual prediction. Returns the
aetherya_verify_predictionRecompute the hash of a sealed prediction and report whether it still matches the stored one.
aetherya_record_outcomeAttach what actually happened to a sealed prediction (append-only) and get the evaluation. creative_comparison actual: {metric:'ctr', values:[{creativeId?|variant?, value, impressions?, clicks?}]}; impressions and clicks let Aetherya record the result for calibration (see calibra
aetherya_create_intake_linkCreate a secret upload link to send a client so they can drop creative files (images, video) for pretesting. Returns the url and expiry; treat the url as a secret and share it only with the client. Needs a workspace admin or manager, and the feature must be enabled for the worksp
aetherya_list_intake_filesList the files a client uploaded through an intake link (name, type, size, status, set label, a short-lived download url). The feature must be enabled for the workspace.
aetherya_list_audiencesList the synthetic audiences (simulated personas) in this workspace: their overall shape (where they are, what they do, how much is actually filled in) plus a sample with ids. These are simulated personas, not real people, and a stored persona pool is usually narrower than the au
aetherya_create_audienceCreate synthetic-audience personas to simulate against. Describe who you want to model and get back personas (with ids) you can then target as the 'audience' in aetherya_audit_site, aetherya_test_copy, or aetherya_ask_audience. These are SIMULATED personas (engine-generated), not
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리에 소스 저장소가 없어서, 게시자(aetherya.ai)와 코드를 맞춰 볼 수 없어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
672ms 만에 응답(HTTP 200)
로그인 필요 없음
도구 설명 27개를 읽었고, AI에게 보내는 숨겨진 지시는 없었어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 3개 중 2개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: AETHERYA_API_KEY, Authorization
둘 다 가능해요. 내 컴퓨터에 설치해도 되고, 클라우드 버전에 연결해도 돼요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.5)은 19일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
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.
저장소에서 README를 찾지 못했어요