Social intelligence for 8 networks: read posts, creators and trends, then create from them.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
Not yet automatically verified
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.
Manual Client & Custom JSON ConfigExpand JSON ▾
Client Config & Setup
Choose your client or environment
Target File:
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Documentation Overview
@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:
Claude Code / CLI without the plugin:
Cursor / any stdio MCP client (claude_desktop_config.json, .mcp.json, …):
Tools
64 tools, grouped by what you are trying to do. Prices are in nooticr credits and match what the server actually charges.
Seven of them — the ones 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_media | 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, and far cheaper than watching the video; everywhere else the post's own audio is transcribed, which needs speech-to-text configured on the server. 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_fast | 2 | The post's transcript, caption and stats — everything but the pictures, which is what makes it the cheap read. Two fetches: get_social_media (1) and get_post_transcript (1). The sensible default. |
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. |
analyze_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. |
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_analysis | free | Draws the analysis your model wrote from analyze_post/analyze_post_fast/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_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_media at 1 credit each. Use when performance differs and you need to know why. |
show_comparison | free | Draws the comparison your model wrote from compare_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
Related MCP Servers
Reviews
No reviews yet — be the first to share how this listing worked for you.
Frequently Asked Questions about Orchyn
AllMCPs Directory Badge
Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.
Badge Style:
Live Dynamic SVG Preview
Markdown (GitHub README)
[](https://allmcps.com/mcp/orchyn)HTML Embed
<a href="https://allmcps.com/mcp/orchyn"><img src="https://allmcps.com/api/badge/orchyn?style=directory" alt="Orchyn on AllMCPs" /></a>Technical Specs & Signals
CategoryDeveloper Tools
36Quality signal: Fair · 36/100How this signal is calculated ▾
Server availabilityNot measured
Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.
Verified ownership10/20
Documentation & tools16/30
Adoption & activity1/15
Community engagement0/10
A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.
Own this project?
This directory is pre-filled from public sources. Claim via GitHub README, site badge, or DNS TXT to unlock edit access and the Official badge — proof is checked automatically, then reviewed by our team.
Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.
Claim & get free dofollowShare & Embed
Add our SVG badge (dark/light directory styles) or embeddable widget to your site.