프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

Orchyn

제작자: orchynX버전 1.26.17i★ –i컴퓨터 또는 클라우드
레지스트리 이름com.orchyn/mcp

설치

개요

제작자가 쓴 설명(영어 원문)

Social intelligence for 8 networks: read posts, creators and trends, then create from them.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 컴퓨터 또는 클라우드
  • 전송 방식: stdio, Streamable HTTP
  • 카테고리: 기타

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 제작자의 서버에서 실행돼요. 내가 요청한 내용은 제작자의 서버를 거쳐요.
  • 레지스트리에 입력해야 할 키가 나와 있지 않아요.

필요한 것

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:

  1. Settings → Connectors 열기
  2. Add custom connector 누르기
  3. 아래 주소를 붙여 넣고 Add 누르기
  4. 로그인하라고 하면 제작자의 서비스에 로그인하기
SettingsConnectors1+ Add2https://…3
https://mcp.orchyn.com/mcp

또는 내 컴퓨터에서 실행하기

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "orchyn": {
      "command": "npx",
      "args": [
        "-y",
        "@orchyn/mcp"
      ]
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add --transport http orchyn https://mcp.orchyn.com/mcp

또는 내 컴퓨터에서 실행하기

claude mcp add orchyn -- npx -y @orchyn/mcp

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "orchyn": {
      "url": "https://mcp.orchyn.com/mcp"
    }
  }
}

또는 내 컴퓨터에서 실행하기

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "orchyn": {
      "command": "npx",
      "args": [
        "-y",
        "@orchyn/mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "orchyn": {
      "type": "http",
      "url": "https://mcp.orchyn.com/mcp"
    }
  }
}

또는 내 컴퓨터에서 실행하기

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "orchyn": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@orchyn/mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:

  1. 웹에서 ChatGPT 열기 → Settings → Connectors (Apps)
  2. Create 또는 Add 누르기(일부 요금제는 먼저 Advanced에서 Developer mode를 켜야 해요)
  3. 아래 주소를 붙여 넣고 이름을 정한 뒤 저장하기
  4. 로그인하라고 하면 제작자의 서비스에 로그인하기
SettingsConnectors1+ Create2https://…3
https://mcp.orchyn.com/mcp

메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 도메인 orchyn.com 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    엔드포인트 응답

    아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요

  • … 아직 점검 안 함

    OAuth로 로그인

    아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요

기타 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 32489개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 32489개 중 32%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 32489개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

Orchyn, 안전한가요?

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.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

둘 다 가능해요. 내 컴퓨터에 설치해도 되고, 클라우드 버전에 연결해도 돼요.

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.26.17)은 2개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

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.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Whisper

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Spec Driven Development

제작자: formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

내 컴퓨터에서 실행★ 440MIT14개월 전 업데이트
설치

Remote Desktop Commander

제작자: desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

클라우드에서 실행★ 211어제 업데이트
설치

Whisper

제작자: whisper-sec

One routable IPv6 per AI agent, verifiable from the DNS root. Keyless tools need no signup.

컴퓨터 또는 클라우드오늘 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

@nooticr/mcp

MCP (Model Context Protocol) server for nooticr.

Gives an AI assistant three things: it can read real social posts across ten networks (TikTok, Instagram, YouTube, X, Reddit, LinkedIn, Douyin, Xiaohongshu, Weibo, Bilibili), understand them — transcript, video frames, comments, the numbers — and make something from what it learned: hooks, variants to film, a scored draft, a repurposed thread.

The understanding is your model's, not ours. Every tool here fetches material and hands it over with an account of what to do with it; none of them ask a model of ours for an opinion first. You pay for the fetch and nothing else.

It also monitors a name: search_mentions sweeps nine of those networks for every comment that says your brand, inside a date window you choose, and search_spoken_mentions reads the words actually said out loud in TikTok, YouTube and Douyin videos for the mentions that were never typed anywhere.

Runs over stdio locally or as a hosted connector at https://mcp.nooticr.com/mcp. Billed against your nooticr credits; new accounts get 20 free.

Install (one link)

Claude Code — register the marketplace, then install the plugin:

/plugin marketplace add Nooticr/nooticr-mcp

/plugin install nooticr@nooticr

Claude Code / CLI without the plugin:

claude mcp add nooticr --user -- npx -y @nooticr/mcp

npx @nooticr/mcp login # one-time sign-in (Google)

Cursor / any stdio MCP client (claude_desktop_config.json, .mcp.json, …):

{

"mcpServers": { "nooticr": { "command": "npx", "args": ["-y", "@nooticr/mcp"], "env": { "NOOTICR_BASE_URL": "https://api.nooticr.com" } } } }

Tools

170 tools, grouped by what you are trying to do. Prices are in nooticr credits and match what the server actually charges.

The job tools under Answer a question you actually have are not endpoint wrappers. Each names a job, fans out over the calls that job needs, groups the evidence by whatever you are deciding about, gives every item an id a follow-up tool can act on, and hands the reading to your model rather than to ours. They fan out, so they cost the sum of what they fetched and every one of them caps that fan-out with an argument.

Read a post
ToolCreditsWhat it is for
get_social_post1The post's facts and media — contentType, title, caption, author, stats, direct media URLs, plus an inline thumbnail. Use when you want the post itself and nothing interpreted.
get_post_transcript1The words actually spoken. Where the platform publishes a caption track (TikTok, Douyin, YouTube) it is read as-is — exact rather than inferred, without processing the video; everywhere else, and where a caption track is missing, the post's own audio is transcribed on the same call (posts up to 30 minutes), which needs speech-to-text configured on the server. No transcript, no charge. format: "srt" or "vtt" also returns a ready caption file built from the track's own timing, at no extra cost. Use before any analysis when the wording matters.
get_post_frames2Frames sampled evenly across a post's video, returned as images you can actually look at — not a description of them. ffmpeg opens the stream directly rather than downloading it, so HLS works and an expired link is re-resolved on the spot. Verified live at 3/3 on TikTok, YouTube, Instagram, Douyin and X; Reddit works on video posts. A carousel or slideshow returns its own images unchanged. Each frame costs roughly 1,200 tokens of your context.
get_post_comments2Top comments plus the themes the platform clusters them into, with which ones the creator pinned or liked. Use when you want to read what people wrote.
Understand a post
ToolCreditsWhat it is for
analyze_post_text2The post's transcript, caption and stats — everything but the pictures. Two fetches: the post itself (1, as get_social_post) and get_post_transcript (1). Use when the words and numbers answer the question.
analyze_post3Frames sampled across the video, as images your model can actually look at, plus the transcript. Two fetches: get_post_frames (2) and get_post_transcript (1). Use when the visuals are the point — framing, editing, on-screen text.
understand_social_post3The same two fetches, asked for a description of what physically happens on screen rather than why it works. Use when you need the events, not the strategy.
summarize_post_comments2The comment section, every comment with a stable id, and the taxonomy to label them with — sentiment, and whether each is praise, a complaint, a bug report, a question, a request, a comparison or spam. The same get_post_comments call, at the same price as reading them directly. Pass verbatim: true to have every item rendered whole for quoting rather than clipped to fit; same price.
show_comment_reviewfreeDraws the classifications your model produced — every comment with its sentiment and category, filterable and selectable. Makes no requests; it only renders what you pass it.
show_post_analysisfreeDraws the analysis your model wrote from analyze_post/analyze_post_text/understand_social_post — hook strength, script structure, quotable lines, suggested hashtags and more, whichever fields you produced. Makes no requests; it only renders what you pass it.
compare_social_posts1The first of two to five posts, fetched with its stats, and the comparison left to you. Fetch the rest with get_social_post at 1 credit each. Use when performance differs and you need to know why.
show_compared_postsfreeDraws the comparison your model wrote from compare_social_posts — each post scored, the winner marked, what differed and the next test worth running. Makes no requests; it only renders what you pass it.
Research a niche or a creator
ToolCreditsWhat it is for
discover_social_posts2Recent posts for a niche across nine networks, with inline thumbnails and limit/offset pagination. Use to find posts to look at.
get_user_posts2One creator's recent posts with stats. Use to scan an account.
search_creators2People by what they make — designers, developers, photographers, anyone with an audience — found by craft, niche or keyword. Use when you know the kind of person but not their names. Searches TikTok, Instagram and Xiaohongshu; not YouTube, Douyin, X, Reddit or LinkedIn, which cannot be creator-searched upstream.
get_similar_creators2Lookalikes for a creator that already works.
suggest_creator_identity2 per network searched, plus 2 to find the handle (6 by default)The same person on the other networks, from one handle you already know — with the evidence for each: a link published in both bios, one bio naming the other account, an identical handle, a matching display name. Suggests, never merges: nothing is stored, a human confirms, and two accounts' follower counts are never added together. TikTok, Instagram and Xiaohongshu.
discover_sounds2Trending audio with playable previews. Sound is a major ranking signal on TikTok.
discover_hashtags2What to tag with. TikTok comes from the Creative Center trend board — volumes plus rising/cooling/steady. The other eight searchable networks have no trend board upstream, so tags are counted across a live sweep of a niche you name: real and current, but a single sample, so no rising/cooling signal. source says which you got. LinkedIn cannot be swept.
find_hook_pattern2A creator's recent posts, so their opening lines can be read as a set and turned into fill-in-the-blank templates. One get_user_posts call.
search_mentions2 per network (5 for Xiaohongshu)Brand monitoring. Every *comment* that names a term, across nine networks at once, grouped under the post it was left on. A brand is named far more often in the replies than in a caption, so the comment is the unit — not the post. Takes a since date to read a past window, and pages with offset/pageSize so a nine-network sweep does not arrive all at once. Does not read speech inside a video — search_spoken_mentions does, on TikTok, YouTube and Douyin.
watch_creatorfreeAdd a creator to your watchlist. Stores the handle only — nothing is fetched.
unwatch_creatorfreeDrop a creator from the watchlist.
list_watchlistfreeWho you are watching: handle, platform, note, and when you last caught up on each — and which saved creator identity each account belongs to, grouped as one person in byIdentity.
save_creator_identityfreeOnce the user has confirmed that accounts on different networks are one person (for instance from suggest_creator_identity's evidence), save them as one creator identity: name, accounts (each {platform, handle, evidence?}), note. Stores exactly what it is given; an account already in another identity is refused with that identity named, never moved.
list_creator_identitiesfreeEvery creator identity your workspace has saved, with its accounts and the evidence recorded for each. Where an identityId comes from.
update_creator_identityfreeRename a saved identity, change or clear its note, or add and remove accounts. An identity keeps at least one account.
delete_creator_identityfreeDelete a saved identity. Only the grouping goes: the accounts and their watchlist entries stay.
watch_creator_identityfreeWatch a person rather than one account: every account of a saved identity goes on your watchlist as its own entry with its own baselines, grouped under the identity. Nothing is fetched.
unwatch_creator_identityfreeTake every account of a saved identity off your watchlist. Accounts watched on their own stay.
catch_up_watchlist2 per creatorWhat everyone you watch has posted since your last catch-up. Compares against the snapshot taken last time and moves it forward, so it answers "what is new" rather than "what exists".
create_brand_watchfree to callSchedule a recurring sweep and get emailed only what is new. kind: "mentions" (default) is a recurring search_mentions sweep for term/platforms; kind: "competitor" is a recurring get_user_posts check on one creator (handle/platform), mailing only what beats their own recent median; kind: "report" runs job: {tool, args} — niche_report (mailed as written every run) or discover_social_posts (only unseen posts) — on the schedule; kind: "portfolio" sweeps up to 25 terms (your brand, products, competitors) across the same networks under one budget and mails one digest with each term's share of voice. Two calls by design: the first returns the quote (cost per run, cadence, cost per day) and a confirmationToken; nothing is created or charged until you call it again with confirm: true and that token. Each run then bills what the server charges for that work — 2 credits per network (5 for Xiaohongshu) for mentions, a flat 2 credits for competitor, for a report 3 for niche_report (a run writes the report it mails, where the niche_report tool here hands the posts to your model for 2) or 2 for discover_social_posts (plus 1 per post opened for comments), and a mentions sweep per term for a portfolio — whose budget is split evenly and trims networks, never terms, and which refunds any term whose sweep fails. appIds ties a watch to products of your workspace (send it on both calls); without it the watch is workspace-wide.

| list_brand_watches | free | Every brand-monitoring watch in your workspace (your teammates' included): term, networks, cadence, cost per run, credits sp

앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요

PopNx에게 묻기