Orchyn

Name: Orchyn
Author: orchynX

作者：orchynX版本 1.26.17i★ –i电脑或云端

注册名称com.orchyn/mcp

安装

概览

作者提供的说明（英文原文）

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

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。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

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: 电脑或云端
传输方式: stdio, Streamable HTTP
分类: 其他

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
在作者的服务器上运行：你向它提出的内容会经过他们的服务器。
注册中心没有列出需要填写的密钥。

你需要

在云端运行无需安装任何东西，通过互联网连接
npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

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 …”。

适用于网页版、桌面版和手机版 Claude：

打开 Settings → Connectors
点击 Add custom connector
粘贴下面的地址，然后点击 Add
如果要求登录，请登录作者的服务

https://mcp.orchyn.com/mcp

或者在你的电脑上运行

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

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

在终端中运行这条命令

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

或者在你的电脑上运行

claude mcp add orchyn -- npx -y @orchyn/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": {
    "orchyn": {
      "url": "https://mcp.orchyn.com/mcp"
    }
  }
}

或者在你的电脑上运行

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": {
    "orchyn": {
      "command": "npx",
      "args": [
        "-y",
        "@orchyn/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": {
    "orchyn": {
      "type": "http",
      "url": "https://mcp.orchyn.com/mcp"
    }
  }
}

或者在你的电脑上运行

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": {
    "orchyn": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@orchyn/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。

ChatGPT 只能连接互联网上的服务器：

打开网页版 ChatGPT → Settings → Connectors (Apps)
点击 Create 或 Add（部分套餐需要先在 Advanced 中开启 Developer mode）
粘贴下面的地址，起个名字，然后保存
如果要求登录，请登录作者的服务

https://mcp.orchyn.com/mcp

菜单名称可能因套餐和版本不同而略有差异。

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

我们还没有读取这个服务器的工具列表；我们会轮流检查各个端点。

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
注册名称已通过域名 orchyn.com 验证（注册中心会核实域名所有权）
… 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
… 尚未检查
端点有响应
尚未检查；我们会轮流检查各个端点
… 尚未检查
使用 OAuth 登录
尚未检查；我们会轮流检查各个端点
… 尚未检查
工具描述中没有隐藏指令
尚未检查；我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

星标数多于此分类中其他 32568 个服务器的 0%
发布到注册中心的时间比此分类中其他 32568 个服务器的 32% 更新
基础检查结果等于或优于此分类中其他 32568 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

Orchyn 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？

两种方式都可以：安装在你的电脑上，或者连接云端版本。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（1.26.17）于2个月前进入注册中心。

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。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。

有什么可以替代它？

同一分类中有：Spec Driven Development, Remote Desktop Commander, FlyDocs

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

Spec Driven Development

作者：formulahendry

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

在你的电脑上运行★ 440MIT14个月前更新

安装

Remote Desktop Commander

作者：desktop-commander

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

在云端运行★ 211昨天更新

安装

FlyDocs

作者：flydocs.ai

Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.

在你的电脑上运行今天更新

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。

@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

Tool	Credits	What it is for
`get_social_post`	1	The 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_transcript`	1	The 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_frames`	2	Frames 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_comments`	2	Top 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

Tool	Credits	What it is for
`analyze_post_text`	2	The 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_post`	3	Frames 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_post`	3	The 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_comments`	2	The 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_review`	free	Draws 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_analysis`	free	Draws 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_posts`	1	The 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_posts`	free	Draws 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

Tool	Credits	What it is for
`discover_social_posts`	2	Recent posts for a niche across nine networks, with inline thumbnails and `limit`/`offset` pagination. Use to find posts to look at.
`get_user_posts`	2	One creator's recent posts with stats. Use to scan an account.
`search_creators`	2	People 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_creators`	2	Lookalikes for a creator that already works.
`suggest_creator_identity`	2 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_sounds`	2	Trending audio with playable previews. Sound is a major ranking signal on TikTok.
`discover_hashtags`	2	What 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_pattern`	2	A 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_mentions`	2 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_creator`	free	Add a creator to your watchlist. Stores the handle only — nothing is fetched.
`unwatch_creator`	free	Drop a creator from the watchlist.
`list_watchlist`	free	Who 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_identity`	free	Once 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_identities`	free	Every creator identity your workspace has saved, with its accounts and the evidence recorded for each. Where an `identityId` comes from.
`update_creator_identity`	free	Rename a saved identity, change or clear its note, or add and remove accounts. An identity keeps at least one account.
`delete_creator_identity`	free	Delete a saved identity. Only the grouping goes: the accounts and their watchlist entries stay.
`watch_creator_identity`	free	Watch 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_identity`	free	Take every account of a saved identity off your watchlist. Accounts watched on their own stay.
`catch_up_watchlist`	2 per creator	What 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_watch`	free to call	Schedule 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

只显示了开头部分；其余内容请在仓库中阅读

Orchyn

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

或者在你的电脑上运行

或者在你的电脑上运行

或者在你的电脑上运行

或者在你的电脑上运行

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“其他”中的其他服务器比较i

常见问题

替代选择

Spec Driven Development

Remote Desktop Commander

FlyDocs

作者的 README

@nooticr/mcp

Install (one link)

Tools

Read a post

Understand a post

Research a niche or a creator