Orchyn
Overview
Description from the maker (original English)
Social intelligence for 8 networks: read posts, creators and trends, then create from them.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiVery new↓ 66/wk · ★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Computer or cloud
- Transport: stdio, Streamable HTTP
- Category: Marketing & social media
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on the maker’s server: what you ask it goes through their server.
- The registry lists no key to fill in.
You need
- Runs in the cloudNothing to install; it connects over the internet
- npmNode.js installed (for the npx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Works in Claude on the web, desktop and mobile:
- Open Settings → Connectors
- Press Add custom connector
- Paste the address below and press Add
- If it asks you to sign in, sign in with the maker
https://mcp.orchyn.com/mcpOr run it on your computer
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"orchyn": {
"command": "npx",
"args": [
"-y",
"@orchyn/mcp"
]
}
}
}Run this in your terminal
claude mcp add --transport http orchyn https://mcp.orchyn.com/mcpOr run it on your computer
claude mcp add orchyn -- npx -y @orchyn/mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"orchyn": {
"url": "https://mcp.orchyn.com/mcp"
}
}
}Or run it on your computer
Or copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"orchyn": {
"command": "npx",
"args": [
"-y",
"@orchyn/mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"orchyn": {
"type": "http",
"url": "https://mcp.orchyn.com/mcp"
}
}
}Or run it on your computer
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"orchyn": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@orchyn/mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
- Open ChatGPT on the web → Settings → Connectors (Apps)
- Press Create or Add (some plans need Developer mode under Advanced first)
- Paste the address below, give it a name and save
- If it asks you to sign in, sign in with the maker
https://mcp.orchyn.com/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
We have not read this server’s tool list yet; we check endpoints in rotation.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified against the domain orchyn.com (the registry checks domain ownership)
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- … Not checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
- … Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
- … Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint
Compared with others in Marketing & social mediai
- More stars than 0% of the other 3594 servers in this category
- Published to the registry more recently than 29% of the other 3594 servers in this category
- Basic checks equal to or better than 100% of the other 3594 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Orchyn safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
Either way works: install it on your computer or connect to the cloud version.
Is it still maintained?
The GitHub repo last changed –, and the latest version (1.26.17) reached the registry 2 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
What can I use instead?
In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Google Analytics MCP
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
BibiGPT YouTube Video Summarizer
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
@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/mcpnpx @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
Only the beginning is shown; read the rest in the repo