# Orchyn [Health: Active] **Category:** 💻 Developer Tools **Repository:** https://github.com/orchynX/mcp **GitHub Stars:** 0 **Views:** 0 **Installs:** 0 **Upvotes:** 0 **Directory Page:** https://allmcps.com/mcp/orchyn ## Description Social intelligence for 8 networks: read posts, creators and trends, then create from them. ## Claude Desktop Quick Installation Install path detected from listing signals. Uses `npx` (confidence: high): ```json "mcpServers": { "orchyn": { "command": "npx", "args": ["-y","@nooticr/mcp"] } } ``` ## Documentation & README # @nooticr/mcp MCP (Model Context Protocol) server for [nooticr](https://nooticr.com). 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**: ```bash 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`, …): ```json { "mcpServers": { "nooticr": { "command": "npx", "args": ["-y", "@nooticr/mcp"], "env": { "NOOTICR_BASE_URL": "https://api.nooticr.com" } } } } ``` ## 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 | 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. | | `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. | | `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. 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 the same as calling the matching tool yourself — 2 credits per network (5 for Xiaohongshu) for mentions, a flat 2 credits for competitor. | | `list_brand_watches` | free | Every watch you have scheduled: term, networks, cadence, cost per run, credits spent so far, runs made, and when the next one is due. | | `mention_trend` | free | **What a watch has seen over time**, which nothing else here answers — every other read is about now. One point per run: when it ran, how many mentions it found, how many were new, and both counts per network, so "which network is growing" and "did it go quiet or did we stop looking" come apart. On a competitor watch each point carries the median that run measured, which turns "they beat their own median" into "and that median has doubled". Plus the mentions more than one run has seen. Free because the sweeps were billed when they ran; charging again to read what was already paid for is the thing it fixes. | | `stop_brand_watch` | free | Stop a watch by `watchId` or `term`. Immediate — the next run does not happen and nothing more is charged. | | `niche_report` | 2 | Recent posts in a niche with their stats, so the dominant formats, hook patterns and the gaps nobody fills can be read off them. One `discover_social_posts` call. Use when deciding what to make. | | `analyze_creator_profile` | 2 | A creator's recent posts with their stats — the material of a teardown: niche, themes, hook formula, what over- and underperforms, who the audience is. One `get_user_posts` call. | ### Answer a question you actually have | Tool | Credits | What it is for | |------|---------|----------------| | `answer_my_audience` | 2 + 2 per post opened (14 by default) | **The mirror of `search_mentions`.** The questions waiting under your *own* posts: recent posts fetched, comments read on each, grouped under the post they were left on, every comment with a stable id, and the ones that read like questions or requests flagged and sorted to the top. It finds and drafts — it cannot post a reply, because no nooticr connection carries comment-write permission on any network. `limit` caps how many posts are opened, which is the price. | | `prepare_handoff` | free | **The hand-off to your tracker.** Turns items you classified — a bug report in a comment, a complaint said out loud in a video — into the exact `title`, `body` and `labels` to file through whichever GitHub, Jira or Linear MCP server the host also has connected. nooticr files nothing and holds no tracker credential. The body carries the quote fenced and framed as a third-party report rather than as instructions, because the issue is read next by a coding agent; contact details are redacted, `@handles` and `#numbers` are defanged so filing notifies nobody by accident, and a `searchFirst` string dedupes a second sweep against the first. Makes no requests. | | `show_audience_replies` | free | Lays your drafts out for a person to work through, grouped under the post, each with what you decided to do about it. Sends nothing; fetches nothing. | | `show_standings` | free | Draws the standings your model read out of `compare_creators` or `watchlist_standings` — one row per creator, with the window and the median it was scored against. `ranking` records which axis you ordered on, and `tooThin` draws a creator with too short a window as unranked rather than last: missing from a comparison is not the same as losing it. Makes no requests. | | `show_trend` | free | Draws the trend your model read out of `mention_trend`. `tooShort` marks a series with too few points to call a direction, and `edgeIsRecordStart` marks a left edge that is where the record begins rather than where the conversation did — a chart hiding either is the mistake this view could otherwise make on your behalf. Makes no requests. | | `track_competitor` | 2 | What a creator shipped, and which of it beat **their own** median rather than a raw view count that mostly measures follower count. One post list, whatever the window. If they are on your watchlist it also marks what is new since your last check and moves that marker forward — its own marker, not the one `catch_up_watchlist` keeps. | | `compare_creators` | 2 per creator (4-10) | Two to five creators side by side on the one axis that compares: each post's ratio to **that creator's own** median. Per creator you get the window that was scored, their median, the share of it that beat that median, how hard they beat it when they did, every ratio, and their best and worst post. It does not rank them — "how often they land one" and "how big it is when they do" usually disagree, and a hit rate over a short window is one post either way, so the window travels with every number and the read is yours. | | `watchlist_standings` | 2 per watched creator | The same, across everyone on your watchlist: "who moved" in one call instead of one per creator. Reading the watchlist is free; the fetches are not, so it confirms the total before spending. `catch_up_watchlist` answers what is **new**; this answers how it **did**. | | `who_should_i_work_with` | 2, or 4 with a seed | A collaboration shortlist: a keyword search merged with the lookalikes of a creator who already fits, marked by which search found each one. Every candidate also carries the **links pulled out of their bio**, typed and sorted by how much opening one will tell you — a repository to read the code in, their own site, a link hub that holds the real links — so vetting is reading the work rather than re-reading the follower count. Those links are never fetched here: they came out of a field the person being evaluated controls, so the host opens them, and the result says so. It does **not** measure audience overlap — that costs about nine credits a candidate, so the result says so and shows how to check a finalist rather than faking the signal. | | `show_collab_shortlist` | free | Draws the candidates you scored, ranked, and asks the user which to approach. The scores are attributed to your model, not presented as a nooticr rating, and a candidate scored without anything having been opened is marked unverified. Makes no requests. | | `why_did_this_underperform` | 3 | One post against the creator's own recent distribution, with the post taken back out of its own baseline. Returns median, quartiles, ratio and percentile, so the answer can be "this is an ordinary result, not a failure". Different question from `compare_posts`, which weighs two URLs you already picked. | | `what_should_i_make_next` | 2 + 2 per post read + 2 (12 by default) | Demand against supply: what your commenters explicitly ask for, set beside what a niche sweep shows is already being made. A gap nobody asked for is noise; a request nobody serves is the opportunity. Falls back to your most-used hashtag when you name no niche. | | `search_spoken_mentions` | 2 per platform narrowed by niche + 2 per creator handle + 1 per transcript, up to `maxTranscripts` | **The mirror of `search_mentions`, for what was said rather than typed.** Narrows to candidate posts (a niche sweep, named handles, and/or your watchlist), transcribes only the most-viewed survivors up to a hard ceiling, and searches the words for the term — TikTok, YouTube and Douyin, and only where the creator actually enabled captions. Reports how many candidates were found, transcribed and matched, so the spend is legible. | ### Make something | Tool | Credits | What it is for | |------|---------|----------------| | `write_hooks` | 2, or free | The source post and its transcript, to write openings against. Give a topic instead of a url and it fetches nothing and costs nothing. | | `show_hooks` | free | Draws the hooks your model wrote from `write_hooks` — each one with the device it uses and who it stops. Makes no requests; it only renders what you pass it. | | `score_draft` | free | **Your** draft back with the rubric to hold it to — hook, clarity, payoff, specificity and fit, each scored 1-10, plus the three fixes worth making and a rewritten opening. Fetches nothing: the text is already yours. The only tool that runs before the content exists. | | `repurpose_post` | 2 | The source post and its transcript, to rewrite for other surfaces — X thread, LinkedIn post, carousel slides, YouTube metadata, newsletter. | | `show_repurposed_post` | free | Draws the rewritten copy your model produced from `repurpose_post` — one entry per surface. Makes no requests; it only renders what you pass it. | | `create_variants` | 2 | The post that worked, with its transcript, to build variants from: hook, the angle that changes, ordered shot beats and a CTA. | | `show_variants` | free | Draws the variants your model wrote from `create_variants` — each one's hook, angle, beats and CTA. Makes no requests; it only renders what you pass it. | ### Account | Tool | Credits | What it is for | |------|---------|----------------| | `check_nooticr_credits` | free | Balance and billing URL. | | `nooticr_login` | free | Re-link the account when a call fails with an authentication error. | | `list_social_connections` | free | What you have connected and what each connection is actually allowed to do — read the account, publish a post, manage comments — as yes, no or **unknown**. Unknown means the grant predates scope recording: treat it as "try it", not as a refusal. Also says which platforms can be linked at all, which is a smaller set than the networks nooticr reads. | | `connect_social_account` | free | A link the user opens to connect one account. They approve at the provider in their own browser; nothing is connected until they do, and no credential passes through the tool or the model's context. Each call mints a fresh link — an old one does not work twice. | | `create_product` | free | Create a product in your own workspace — the row every other own-account tool needs before it has anything to work with. Always creates in the calling session's workspace, never one you could name. `name` and `slug` are required; every other field is snake_case and read by exact key, so a camelCase `websiteUrl` lands nowhere. Writes no brand playbook. | | `update_product` | free | Patch a product's fields. An omitted argument leaves its column unchanged, so this cannot blank a field by not mentioning it, and the result lists what was actually written — a misspelled field shows up as one that did not change rather than as a silent no-op. | ### Your own product Everything above reads someone else's content. These read and generate for **your own** — a different product, a different balance (your workspace's plan AI credits, not the personal MCP credits above), billed exactly like the matching dashboard button. | Tool | Credits | What it is for | |------|---------|----------------| | `list_own_apps` | free | Every product in your workspace — call this first when you have more than one and another tool below asks for `appId`. | | `create_product` | free | Create a new product in your workspace — `name`/`slug` required, plus optional `description`, `website_url`, `niche`, `product_type` and store-listing fields (snake_case — see note below). Takes no workspace id; always creates in your own. Does not generate a brand playbook — call `analyze_product` for that. | | `update_product` | free | Patch a product's fields — omitted arguments leave their column unchanged. Same snake_case field names as `create_product`. | | `get_scheduled_posts` | free | Your own scheduled and draft posts in the content pipeline — title, status, scheduled time, approval status. What is queued to publish. | | `get_post_performance` | free | Your own already-published posts with their engagement counters — views, likes, comments, shares, platform, post date. The raw performance history, not an interpretation of it; pair with `growth_brief` for that. | | `get_video_stats` | free | Your own most recently synced video performance stats across every connected creator — views, likes, comments, shares, plus a running total. Reads the last sync; does not trigger a new one. | | `get_content_plan` | free | The saved weekly content plan for a product, if one has been generated. `plan: null` when none has. | | `get_brand_playbook` | free | Your product's brand playbook — name, description and the playbook text — if one has been configured, in the dashboard or by `analyze_product`. Read-only; `available: false` when none exists. | | `review_post` | free | Score a draft before you publish it — hook strength, an A/B hook comparison, aesthetic and storytelling notes, rewritten hooks/captions. Never billed, same as the dashboard's own pre-publish review. | | `draft_post` | plan AI credits | A ready-to-use draft (title, caption, hashtags, per-slide script) for a topic, grounded in your product's name. Returns text only — saves nothing. | | `growth_brief` | plan AI credits | A plain-language brief — the one insight that matters, wins, risks, next actions — grounded in your real post history and synced analytics. | | `generate_content_plan` | plan AI credits | A one-week, day-by-day content plan for your creators, grounded in what already worked. Saved — fetch it later with `get_content_plan`. | | `generate_captions` | plan AI credits | Timed on-screen caption cues for a video — a transcript plus start/end-timed lines. Returns cue data only. | | `analyze_product` | plan AI credits | Start an AI analysis of your product: fetches an excerpt of its own website (a real outbound fetch, not just nooticr's own data), reads its posts and fleet performance, and writes the result as its brand playbook. Runs in the background — returns a `jobId`, poll it with `analyze_product_status`. 10 plan AI credits, first analysis free per workspace. | | `analyze_product_status` | free | Poll a job `analyze_product` started. Returns `state` (pending/thinking/done/error) and, once done, the analysis. Free — the cost was already charged when the job started. | | `list_social_connections` | free | The social accounts you've connected and what each is allowed to do — read, publish, manage comments. Also lists which platforms can be connected at all. | | `connect_social_account` | free | A link to open to connect one account. You approve at the provider; nothing connects until you do, and no credential ever passes through this tool. | ### How billing works - New accounts get **20 free credits**. - **Every tool is priced at what it fetches upstream**, and bills from the first call. A tool that fans out to two fetches costs both — `analyze_post` is 2 for the frames plus 1 for the transcript — and its description says so. There is no free first use: that grant belonged to the AI calls, and there are none. - A call that fails is **refunded automatically**, and a call interrupted mid-flight is billed **once at most** — retries are idempotent. - Platform admins bypass credit debiting entirely. ## Interactive cards in Claude / ChatGPT chat Every tool that returns posts also renders **inline interactive cards** directly in the chat (MCP Apps `ui://nooticr/view` resource rendered in a sandboxed iframe): - **Video posts** (TikTok/IG/YouTube/Douyin/LinkedIn) — an inline `