"author:4714407" matching MCP tools:

• search_contentA

  flevyA

  Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.

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• quizbase_randomA

  QuizBaseA

  Fetch N random trivia questions matching filters. Quality-first: by default excludes questions flagged for review (use quality='all' to include for audit/research). USE WHEN: building a quiz, sampling content for warmup, generating practice sets. NOT WHEN: you need a specific question ID (use quizbase_question_by_id) or want to explore a topic deeply with facets (use quizbase_topic_by_slug). KEY FILTERS: - amount: 1-50, default 10. - lang: ISO 639-1. Default "en". Supported: en, pl. Strict — unknown language returns 400. - category (slug): e.g. geography, history, science-and-nature. Full list via quizbase_categories. - difficulty: trivial | easy | medium | hard | expert. LLM-calibrated. Records not yet LLM-rated hold the importer placeholder (mostly "medium" for factoid sources). - type: multiple | boolean (default both; no text_input in random). - regions (cultural affinity, AND): empty in data = no cultural advantage assumed. Lowercase ISO 3166-1 alpha-2 ('us', 'pl', 'gb') + cultural codes ('jewish', 'christian-catholic', 'islam'). Filter for content statistically more likely known by residents/members. Discover via quizbase_regions. - source (array): include only these source databases (one or more of 12: opentdb, opentriviaqa, kqa-pro, entityq, mintaka, mkqa, nq-open, creak, qasc, arc, webq, quizbase). - exclude_source (array): drop these sources, e.g. ["entityq"] for human-curated only. Applied after source. - license (SPDX): CC-BY-SA-4.0 | CC-BY-SA-3.0 | MIT | etc. Restrict to redistribution-friendly content. - topic (curated slug): higher precision than tags. Alias resolver matches subcategories+tags. List via quizbase_topics. - topics_any: OR over curated topics, max 10. - tags (AND), tags_any (OR), subcategory: raw taxonomy. Use topic if available. - quality: 'high' (default, recommended) = cleanest, most broadly-useful. 'standard' = broader pool incl. niche/too-specific (more volume). 'all' = audit/research, includes flagged — when 'all', each question gains a "quality" field ('high' or 'needs_review'). - exclude (UUIDs, max 250): de-dupe within a quiz session. OUTPUT: { questions: [...], meta: { count, language } }. Each question carries full per-record attribution (source, author, license, licenseVersion, licenseUrl, sourceId, url, modifications, lastModified) — identical shape to REST /api/v1/questions/random. ATTRIBUTION REQUIRED if you redistribute. CC-BY-SA modifications must be credited per § 3(a)(1)(B) using each question's own attribution object. COMMON MISTAKES: forcing lang='pl' for a global audience (use 'en' default); skipping quality (default already excludes flagged content — only pass quality='all' for audit); using tags when a curated topic exists (worse precision).

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• discovery_analyzeA

  DiscoA

  Run Disco on tabular data to find novel, statistically validated patterns. This is NOT another data analyst — it's a discovery pipeline that systematically searches for feature interactions, subgroup effects, and conditional relationships nobody thought to look for, then validates each on hold-out data with FDR-corrected p-values and checks novelty against academic literature. This is a long-running operation. Returns a run_id immediately. Use discovery_status to poll and discovery_get_results to fetch completed results. Use this when you need to go beyond answering questions about data and start finding things nobody thought to ask. Do NOT use this for summary statistics, visualization, or SQL queries. Public runs are free but results are published. Private runs cost credits. Call discovery_estimate first to check cost. Private report URLs require sign-in — tell the user to sign in at the dashboard with the same email address used to create the account (email code, no password needed). Call discovery_upload first to upload your file, then pass the returned file_ref here. Args: target_column: The column to analyze — what drives it, beyond what's obvious. file_ref: The file reference returned by discovery_upload. analysis_depth: Search depth (1=fast, higher=deeper). Default 1. visibility: "public" (free) or "private" (costs credits). Default "public". title: Optional title for the analysis. description: Optional description of the dataset. excluded_columns: Optional JSON array of column names to exclude from analysis. column_descriptions: Optional JSON object mapping column names to descriptions. Significantly improves pattern explanations — always provide if column names are non-obvious (e.g. {"col_7": "patient age", "feat_a": "blood pressure"}). author: Optional author name for the report. source_url: Optional source URL for the dataset. use_llms: Slower and more expensive, but you get smarter pre-processing, summary page, literature context and pattern novelty assessment. Only applies to private runs — public runs always use LLMs. Default false. api_key: Disco API key (disco_...). Optional if DISCOVERY_API_KEY env var is set.

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• formatCitationA

  Scholar SidekickA

  Format scholarly identifiers into a finished citation in a specific style. Use when the user wants a paste-ready citation string for a manuscript, slide, message, footnote, or in-line reference. Style defaults to vancouver if unspecified; ask the user before defaulting if any ambiguity exists (e.g. 'Harvard' and 'Chicago' have multiple variants — confirm which one). Supports five hand-tuned builtins (vancouver, ama, apa, ieee, cse) plus any of 10,000+ CSL style IDs (chicago-author-date, harvard-cite-them-right, modern-language-association, nature, bmj, the-lancet, etc.). Alias and dependent-style resolution apply, so 'harvard' resolves to 'harvard-cite-them-right' and the canonical ID is reported back as styleUsed. Output defaults to text; pass output=html for marked-up HTML or output=json for structured CSL items. Accepts the same identifier formats as resolveIdentifier (DOI/PMID/PMCID/ISBN/arXiv/ISSN/ADS/WHO IRIS, prefixes tolerated), single or comma/newline-separated batch — one round trip per call. Returns: one of { text, html, items } depending on the output parameter, followed by a metadata block ({formatter: 'builtin' | 'csl', styleUsed, requestId, warnings?}) appended as a second text content item — surface this to the user when they care about reproducibility. Use resolveIdentifier instead when the user wants raw metadata to inspect or transform; use exportCitation when they want a downloadable bibliography file. Read-only and idempotent — safe to retry. Works anonymously against the public Scholar Sidekick API (rate-limited free tier); set SCHOLAR_API_KEY (a free ssk_ key from https://scholar-sidekick.com/account) for higher limits, or RAPIDAPI_KEY for paid RapidAPI tiers. Rate limits follow your tier.

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• formatCitationA

  Scholar SidekickA

  Format scholarly identifiers into a finished citation in a specific style. Use when the user wants a paste-ready citation string for a manuscript, slide, message, footnote, or in-line reference. Style defaults to vancouver if unspecified; ask the user before defaulting if any ambiguity exists (e.g. 'Harvard' and 'Chicago' have multiple variants — confirm which one). Supports five hand-tuned builtins (vancouver, ama, apa, ieee, cse) plus any of 10,000+ CSL style IDs (chicago-author-date, harvard-cite-them-right, modern-language-association, nature, bmj, the-lancet, etc.). Alias and dependent-style resolution apply, so 'harvard' resolves to 'harvard-cite-them-right' and the canonical ID is reported back as styleUsed. Output defaults to text; pass output=html for marked-up HTML or output=json for structured CSL items. Accepts the same identifier formats as resolveIdentifier (DOI/PMID/PMCID/ISBN/arXiv/ISSN/ADS/WHO IRIS, prefixes tolerated), single or comma/newline-separated batch — one round trip per call. Returns: one of { text, html, items } depending on the output parameter, followed by a metadata block ({formatter: 'builtin' | 'csl', styleUsed, requestId, warnings?}) appended as a second text content item — surface this to the user when they care about reproducibility. Use resolveIdentifier instead when the user wants raw metadata to inspect or transform; use exportCitation when they want a downloadable bibliography file. Read-only and idempotent — safe to retry. Works anonymously against the public Scholar Sidekick API (rate-limited free tier); set SCHOLAR_API_KEY (a free ssk_ key from https://scholar-sidekick.com/account) for higher limits, or RAPIDAPI_KEY for paid RapidAPI tiers. Rate limits follow your tier.

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• insight_discovery_toolA

  SantimentA

  List Santiment insights (analyst-written crypto articles) published in a lookback window. Returns metadata only — id, title, tags, author, link, published_at, prediction — never the article body. ## When to use - The user asks what Santiment analysts have written or published recently. - As step 1 of a two-step read: discover ids here, then pass them to `fetch_insights_tool` for the full text. ## When not to use - Full text of an insight — use `fetch_insights_tool` (it needs ids, so call this tool first). - What the market is talking about right now — use `trending_stories_tool` (stories only) or `combined_trends_tool` (stories + trending words). Insights are human-authored articles, not live social signal. - Numeric metric timeseries for an asset — use `fetch_metric_data_tool`. - Ranking or screening assets by a metric — use `assets_by_metric_tool`. ## Parameters - `time_period` (optional, default `"30d"`) — lookback window as `<integer><unit>`, unit one of `s`, `m`, `h`, `d`, `w`, `y` (e.g. `"12h"`, `"7d"`, `"90d"`, `"1y"`). The window is always `now - time_period` .. `now`; absolute dates and future ranges are not supported. An unparsable value returns an error, not a default. There is no tag, author, asset or full-text filter — filter the returned list yourself. ## Behavior - Read-only: no writes, no state change, nothing destructive. - Requires an authenticated Santiment account (API key or OAuth token); every call counts against the account plan's MCP rate limits. - Returns only published, moderator-approved insights, newest first, hard capped at 100 per call. A wide `time_period` can hit that cap and silently omit the oldest insights — if `total_count` is 100, narrow the window and call again. ## Response JSON object: { "insights": [ { "id": 1234, // integer, feed to fetch_insights_tool "title": "...", "tags": ["BTC", "bitcoin"], // asset tickers/slugs and topics "link": "https://app.santiment.net/insights/read/1234", "published_at": "2025-01-30T10:00:00Z", "author": "username", // "Anonymous" when unset "prediction": "semi_bullish" // heavy_bullish | semi_bullish | // semi_bearish | heavy_bearish | // none | unspecified | null } ], "time_period": "30d", "total_count": 1, "period_start": "2024-12-31T10:00:00Z", "period_end": "2025-01-30T10:00:00Z" } An empty `insights` list with `total_count: 0` means nothing was published in the window — a valid result, not an error.

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• check_ai_visibilityA

  Superflow Free ToolsA

  Check whether AI assistants (ChatGPT, Claude, Perplexity, Google AI) can reach, read, and cite a web page. Runs the full suite: robots.txt rules per AI crawler, a live firewall test that requests the page as GPTBot, JavaScript dependency, llms.txt, headings, structured data, and author identity. Returns a score out of 100 with a grade, a score per category, and a finding per check with why it matters and how to fix it. Use this for a whole-page verdict; use check_robots_txt_for_ai when the question is only about crawler access. Returns { ok, report: { score, grade, scoredOutOf, categories[], findings[] with why and fix, detection }, cached, ageSeconds }. Limit: 10 runs per hour per IP. Allow up to 75s for a response. Free, no account, no API key. Pass `url` to start a run. A slow run answers with `{ status: "pending", runId }` instead of a result: call this same tool again with just that `runId` to collect it, as many times as it takes. Collecting costs no rate-limit slot.

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• colony_get_user_commentsA

  mcp-serverB

  Every comment by one author, newest first. Answers "what has this account actually said". Until now the only way was to paginate the public firehose looking for a name: every other comment tool takes a post_id, ``colony_search_posts`` returns posts and never comments, and ``colony_get_my_actions`` covers only your own account. Give ``username`` or ``user_id``; each takes a username or a user ID, and both are fine when they name the same account. Bodies come back in full; each row carries ``post_id``. What you see depends on who you are: comments on posts in private colonies are visible only to approved members of those colonies. It also excludes deleted comments and comments on deleted, draft, junk-flagged or approval-pending posts, so it can report fewer than the author's profile page shows. Paginate by passing back ``next_cursor`` from a prior call; it is null when there is nothing further.

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• colony_get_user_commentsA

  The ColonyB

  Every comment by one author, newest first. Answers "what has this account actually said". Until now the only way was to paginate the public firehose looking for a name: every other comment tool takes a post_id, ``colony_search_posts`` returns posts and never comments, and ``colony_get_my_actions`` covers only your own account. Give ``username`` or ``user_id``; each takes a username or a user ID, and both are fine when they name the same account. Bodies come back in full; each row carries ``post_id``. What you see depends on who you are: comments on posts in private colonies are visible only to approved members of those colonies. It also excludes deleted comments and comments on deleted, draft, junk-flagged or approval-pending posts, so it can report fewer than the author's profile page shows. Paginate by passing back ``next_cursor`` from a prior call; it is null when there is nothing further.

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• fetch_page_metadataA

  Razi ToolsA

  Read a web page's metadata without downloading any images. Returns JSON { url, finalUrl, title, description, siteName, canonical, lang, themeColor, author, generator, feeds, openGraph, twitter, icons, cached }, where `feeds` is an array of RSS/Atom URLs, `openGraph` and `twitter` are the complete tag sets as string maps, and any tag the page does not declare is simply omitted. `icons` is always an empty array here because icon resolution is switched off — call fetch_site_logo when the caller wants a logo, favicon or icon. `finalUrl` is the address after redirects (up to 3 hops are followed), which is how you resolve where a domain actually points. This is the fast, cheap counterpart to fetch_site_logo: one page fetch and no image work. It reads the served HTML only — it runs no JavaScript, so a client-rendered page may expose little, and it does not capture how the page looks (use screenshot_url for that). The crawler identifies itself as RaziMetadataBot, and HTTP status is not checked, so a 404 or bot-challenge page that serves HTML is parsed as though it were the page you asked for. Errors: 400 for a URL that is refused as unsafe, redirects too many times, does not return HTML, or exceeds the 5MB page cap; 504 if the page does not answer within 10 seconds; 502 otherwise. Results are cached for 24 hours and replayed with cached: true; 20 calls per minute per IP, then 429.

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• fetch_page_metadataA

  Razi Web ToolsA

  Read a web page's metadata without downloading any images. Returns JSON { url, finalUrl, title, description, siteName, canonical, lang, themeColor, author, generator, feeds, openGraph, twitter, icons, cached }, where `feeds` is an array of RSS/Atom URLs, `openGraph` and `twitter` are the complete tag sets as string maps, and any tag the page does not declare is simply omitted. `icons` is always an empty array here because icon resolution is switched off — call fetch_site_logo when the caller wants a logo, favicon or icon. `finalUrl` is the address after redirects (up to 3 hops are followed), which is how you resolve where a domain actually points. This is the fast, cheap counterpart to fetch_site_logo: one page fetch and no image work. It reads the served HTML only — it runs no JavaScript, so a client-rendered page may expose little, and it does not capture how the page looks (use screenshot_url for that). The crawler identifies itself as RaziMetadataBot, and HTTP status is not checked, so a 404 or bot-challenge page that serves HTML is parsed as though it were the page you asked for. Errors: 400 for a URL that is refused as unsafe, redirects too many times, does not return HTML, or exceeds the 5MB page cap; 504 if the page does not answer within 10 seconds; 502 otherwise. Results are cached for 24 hours and replayed with cached: true; 20 calls per minute per IP, then 429.

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• reddit_searchA

  Veezee: LinkedIn people & company data for agentsA

  Search all of Reddit by keywords. type picks the target: posts (default), comments (what people actually say about a product, problem, or brand -- unique to Reddit search), subreddits (find communities), users. Pass query as free text up to 256 characters; decompose broad topics into several narrower queries, since result depth per query is capped upstream around a few hundred results. sort applies to posts (relevance|top|new|hot|comment_count) and comments (relevance|top|new); range (past_hour..all_time) applies to posts only; both are rejected with INVALID_INPUT elsewhere. Costs 6 credits per page; a cursor page is a NEW call priced the same way. Returns one page of summaries (author, title or comment text, upvotes, comment_count, created_at, permalink, id) with a cursor; there is no server-side time window on comment search, so for monitoring filter on created_at yourself and poll with sort=new. Fetch full post bodies and discussion threads with reddit_get_post; read one community's feed with reddit_get_subreddit_posts. For high-volume recency sweeps across X instead, use x_search.

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• search_articlesA

  Digital Garden by Alicia — NotesA

  Use this when the user asks what Alicia or digitalgarden.si has written about a subject (for example Houdini, Three.js, WebGPU, glTF/USD, Gaussian splats, AI coding agents, or the garden itself). Ranks published notes by keyword match on title, topics, summary and full text, in English and Chinese, and returns short cards (no full text). Follow up with get_article to read one. Do not use it for general web search, news, or topics unrelated to Alicia's published notes. An empty articles array means no published note matches. Scores are relative to this query and catalog, not confidence percentages; check titles and read the full note before presenting a match as relevant. Every result includes canonicalUrl and author Alicia (Person @id https://digitalgarden.si/#alicia). Cite the canonical URL when quoting. digitalgarden.si is an interactive 3D garden, not a knowledge-base wiki.

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• search_articlesA

  Digital Garden by Alicia — NotesA

  Use this when the user asks what Alicia or digitalgarden.si has written about a subject (for example Houdini, Three.js, WebGPU, glTF/USD, Gaussian splats, AI coding agents, or the garden itself). Ranks published notes by keyword match on title, topics, summary and full text, in English and Chinese, and returns short cards (no full text). Follow up with get_article to read one. Do not use it for general web search, news, or topics unrelated to Alicia's published notes. An empty articles array means no published note matches. Scores are relative to this query and catalog, not confidence percentages; check titles and read the full note before presenting a match as relevant. Every result includes canonicalUrl and author Alicia (Person @id https://digitalgarden.si/#alicia). Cite the canonical URL when quoting. digitalgarden.si is an interactive 3D garden, not a knowledge-base wiki.

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• attach_referenceA

  DemandBirdA

  Attach source material to a post (a call transcript, an article, notes) so it is stored WITH the post and readable by the author and reviewers, WITHOUT any of it going into the post copy. Use this for anything the post was written from. NEVER paste a transcript or source text into `content` on save_draft/update_draft; that publishes it. Give exactly one of `text` (the material itself) or `url` (a link we fetch in the background). Makes no AI call, changes no post copy, and does not reset an approval. A post holds at most 20 references.

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• comment_on_postA

  DemandBirdA

  Leave a comment on a post the user is reviewing, wrote, or can see as an admin. It decides and blocks nothing: for a verdict use approve_post or send_back_post. Use for feedback, a question, or a note. The text is stored verbatim, so pass the user's own words. The author and the other reviewers are notified. Ids come from list_posts_awaiting_my_review or list_drafts.

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• connect_onboardA

  bookstore4agentsA

  Start (or resume) Stripe Connect onboarding so this account can RECEIVE author royalties. Returns a one-time onboarding_url the human author must open in a browser to complete KYC. Required before a book can be published: an author with no payouts-enabled Connect account can save drafts but their books stay in draft until onboarding finishes. Payouts stay disabled until Stripe verifies the details — poll connect_status afterward.

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• quizbase_listA

  QuizBaseA

  Cursor-paginated browse over the catalog. Quality-first: by default excludes questions flagged for review (use quality='all' for full pool). USE WHEN: full catalog sync, delta sync (updated_since), exhaustive enumeration by filter. NOT WHEN: you only need N random samples (use quizbase_random) or a single record (use quizbase_question_by_id). PAGINATION: stable cursor over id UUIDv7 DESC. First call: omit cursor. Next: pass meta.nextCursor. Stop when nextCursor is null. KEY FILTERS (full parity with REST): - lang: ISO 639-1, default "en". Supported: en, pl. - category (slug), difficulty (trivial|easy|medium|hard|expert — LLM-calibrated), type (multiple|boolean), subcategory (raw slug). - tags (AND), tags_any (OR, max 10): raw tag slugs. - topic (curated, alias resolver), topics_any (OR over curated): higher precision than tags. - regions (cultural affinity, AND): empty = no cultural advantage assumed. Lowercase ISO 3166-1 alpha-2 ('us', 'pl', 'gb') + cultural codes ('jewish', 'christian-catholic', 'islam'). Filter for content statistically more likely known by residents/members. Discover via quizbase_regions. - source (array): include only these of 12 (opentdb, opentriviaqa, kqa-pro, entityq, mintaka, mkqa, nq-open, creak, qasc, arc, webq, quizbase). - exclude_source (array): drop these sources, e.g. ["entityq"]. Applied after source. - license (SPDX): e.g. CC-BY-SA-4.0, MIT. - quality: 'high' (default) = cleanest, most broadly-useful. 'standard' = broader pool incl. niche/too-specific. 'all' = full pool incl. flagged; when 'all', each question gains a "quality" field ('high' or 'needs_review'). - updated_since (ISO 8601): only questions updated after this — for delta sync caches. BATCH + TRANSLATION MAPPING: - ids (up to 250): fetch those exact records in one call (anti-repeat, deep-links, restoring a saved set). Terminal selector — browse filters and cursor are ignored. Missing ids → meta.missing. - content_language (en|pl): with ids, returns each question's sibling in that CONTENT language across the translation chain — the same questions in another language. Distinct from lang (labels only). PAGINATION + COUNTING: - cursor (string): from previous meta.nextCursor. Omit for page 1. - limit (1-100, default 20). - count: none (default, skip — page via nextCursor) | exact (precise COUNT(*), index-only ~25-90ms). OUTPUT: { questions: [...], meta: { count, countMode, language, nextCursor, total? } }. Each question carries full per-record attribution (source, author, license, licenseVersion, licenseUrl, sourceId, url, modifications, lastModified) — identical shape to REST /api/v1/questions. ATTRIBUTION REQUIRED if you redistribute. Credit each question using its own attribution object — see license + licenseUrl + modifications fields per record. COMMON MISTAKES: not passing the cursor on subsequent calls (you'll re-read page 1); polling without updated_since when doing delta sync.

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• searchCollaboratorsA

  qubitsok — Quantum Computing Jobs, Papers & ResearchersA

  Find quantum computing researchers and potential collaborators from 1000+ active profiles. Use when the user asks about specific researchers, who works on a topic, or wants to find collaborators. NOT for jobs (use searchJobs) or papers (use searchPapers). AI-powered: decomposes natural language into structured filters (tag, author, affiliation, domain, focus). Returns profiles with affiliations, domains, publication count, top tags, and recent papers. Data from arXiv papers published in the last 12 months. Max 50 results. Examples: "quantum error correction researchers at Google", "trapped ions", "John Preskill".

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• get_skillA

  BytesAgain AI Skills SearchA

  Fetch full details for one skill by slug. Call AFTER search_skills or popular_skills when a user selects a specific result — do NOT batch-call for every item. Returns: name, description, category, tags, version, author, downloads, stars, install_command, homepage_url, repo_url. Error lifecycle: slug not found → {error: "Skill not found"} → fall back to search_skills with related keyword. Never guess slugs; only use slugs from prior tool results.

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• ayah_translationA

  Tarteel MCP ServerA

  DEFAULT tool for user-facing translation display. Use this for ANY user-facing request to show/see translations of a Quran ayah — including 'show me…', 'what's the translation of…', 'give me Saheeh/Clear Quran/Taqi Usmani translations of…'. This is the FINAL tool call for these requests; do not follow it with get_translation_text. ONLY skip this widget and use get_translation_text when EITHER (a) the user explicitly asks for plain text / raw text / text-only output, OR (b) the result will be piped into another tool in the same turn without being shown to the user. When in doubt, use this widget. SLUG HANDLING: If the user names a specific translator (e.g. 'Saheeh International', 'Clear Quran', 'Yusuf Ali', 'Pickthall'), ALWAYS call lookup_translations first to resolve the exact slug — do not guess the slug from the author name. Guessed slugs routinely fail validation (the naming isn't fully pattern-based: it's 'en-sahih-international' but 'clearquran-with-tafsir'). You may also pass language codes via 'languages' if the user only specifies a language. Each query must include at least one of languages or translations. Use ayah keys in 'surah:ayah' format (for example '2:255'). In queries[].languages use ISO 639-1 codes (for example 'en', 'ur'), not language names. Do not use 'ar'; Arabic translation is unsupported in this tool.

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