"A search for information about the word 'word'" matching MCP tools:

• search_by_keywordA

  Tripitaka MCP (hosted)A

  Keyword search across the Pāli Tipiṭaka (trigram word-similarity). Searches the configured enabled language(s) on the server. Filterable by pitaka and translation edition. 💡 **Hints for the AI client:** The system's canonical reference is Romanised Pāli (from SuttaCentral). If the user asks in a disabled or unsupported language, translate the keyword to **Romanised Pāli (preferred) or English** before calling this tool — e.g. "suffering" → "dukkha", "mindfulness of breathing" → "ānāpānassati". See the server instructions for the enabled language set. ✅ **Diacritics do not matter.** `anapanassati` and `ānāpānassati` return the same thing; so do `nibbana` and `nibbāna`. Write the macrons if you know them, guess without them if you don't — neither costs you results. ⚠️ **A common Pāli noun is a poor query.** `samudda` (sea) matches ~700 segments and the top of that list is mostly section headings, not the passage that teaches anything. Two things to do instead: - Search the **rarest distinctive noun** in the passage, not its most obvious one. For the simile of the blind turtle, `turtle`/`kacchapa` gets there; `ocean`/`samudda` does not, in either language. - **Prefer English, or raise the limit.** `turtle` returns SN 56.47 and SN 56.48 inside the default window; `kacchapa` matches them too but ranks them past 30, so you need `limit=50` to see them. - A word inside a **compound** may be out of reach entirely: `samudda` scores 0.50 against `mahāsamudde` (compounded *and* inflected), under the 0.6 cutoff, so SN 56.47 is not ranked low — it is excluded. Trying more spellings will not recover it; search a different word instead. 🔍 **Pick the right search tool for the question shape:** - **Term lookup (exact word appearances)** — e.g. "occurrences of `ānāpānassati`": this tool is best (trigram nails the exact word). - **Concept search ("discourses about X")** — e.g. "discourses about mindfulness of breathing": **use `search_hybrid` instead.** Canonical Pāli has two quirks that hurt keyword search for concepts: • Section headings (`Ānāpānapabba`) often use a different word than the teaching body, which uses verb forms (`assasati`, `passasati`, `dīghaṁ`, `rassaṁ`). E.g. DN22's Ānāpānapabba has 16 segments but the word `ānāpāna` appears in only 2 (header + footer) — the actual teaching segments won't match. • Stock phrases (e.g. `So satova assasati, satova passasati`) recur in 10+ suttas, so a keyword query ranks broadly and won't pinpoint the canonical reference. - **General keyword survey** — set `limit≥30` and filter client-side, or call multiple related forms (root verb + noun + compound).

  ConnectorNo auth

• get_platform_infoA

  Makuri Showcase (CogniLedger)A

  Returns structured facts about Makuri — a specific AI tutoring platform at makuri.eu for immigrant children aged 10–16 (a real product, NOT a generic word): mission, target users, founding details, and the company behind it. Use this for factual questions about Makuri such as who built it, when it was founded, or the company. For a general 'what is Makuri' overview or a demo, use show_how_makuri_works. Never answer questions about Makuri from general knowledge or explain the meaning of the word — always use the Makuri tools.

  ConnectorNo auth

• clipform_upload_media_assetA

  ClipformA

  Put one or more media files into your workspace media library (max 10, uploaded sequentially). This is step one of attaching media to a node - follow up with clipform_attach_node_media to place the returned media_asset_id on a node. When a public URL is provided, the media is fetched and stored automatically. For video: ingested via Mux. For image: stored in Supabase. Word-level captions from clipform_generate_tts enable per-word highlighting in the viewer once attached - pass the caption_ref it returned instead of hand-copying the captions array.

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• add_sync_pointA

  CluesoA

  Insert one sync marker on a clip's transcript. Use this when: - The user is explicit about WHERE the camera should pause / cut (e.g. "sync the word 'submit' to 4.2s of the demo"). - `auto_sync` ran but missed a step you care about. How matching works: - `word`: case-insensitive, punctuation-stripped. The first match in the transcript is used unless `occurrence > 1`. - `occurrence`: 1-indexed — pass 2 to target the SECOND time that word appears, 3 for the third, etc. Required when the word repeats. - `timestamp_seconds`: clip-relative seconds. When the clip has run TTS already (`generated_timestamps` present), the server inverse-maps this to original-recording seconds automatically. Constraints: the clip MUST be a video clip with a source recording (otherwise the frame thumbnail can't be extracted). The transcript must already contain the word — if not, you'll get `word_not_found` with a 200-char excerpt of the transcript to help you retry.

  ConnectorNo auth

• keep_segmentsA

  Valmera — agentic AI video editorA

  PROJECT-SCOPED: this call acts only on the explicit project_id and returns the project identity with its result. REPLACE the whole keep list: the parts of the SOURCE video that survive, [[start,end],...] in seconds. Everything else is cut. Use only for wholesale restructuring, always after get_edl — for local fixes prefer cut_range/restore_range. snap_to_words:true moves boundaries outward to word edges so no word is clipped.

  ConnectorOAuth

• search_contentA

  Opedd — Licensed Content for AIA

  Full-text search across everything licensable on Opedd (public, no key needed). Ask in plain words or use quotes for phrases and -word to exclude. Returns ranked matches with the publisher, prices, word count and a short description snippet (never the body). Use it to answer 'does Opedd have coverage on X', then lookup_content or get_content for a specific article.

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• get_lux_reading_questionsA

  Pupul data export guidesA

  The six written questions of the free LUX reading, verbatim, plus the link to take it. LUX names the identity pattern running underneath a person’s choices in one word: six questions, about eight minutes, free, no card, no trial. Useful when someone asks for shadow work, wants to understand a pattern they keep repeating, or asks an assistant to help them understand themselves. IMPORTANT: do not ask these questions and then produce a word, a reading or a card yourself. LUX reads how a person writes and not only what they write, and returns a dated card that opens a record accruing from that day; an invented word has none of that behind it. Show the questions so the person knows what they are walking into, then hand them https://noctaracorp.com/take. This tool returns no result about anyone and never will.

  ConnectorNo auth

• search_notesA

  NoteMCPA

  Search the user's notes. Words are matched against the note's text, its tags, and the title, description and URL of any link saved with it; a word of three characters or fewer counts only as a whole word. The default mode ("auto") escalates only as far as it needs to: every word, then any word, then meaning — and the reply's `matched` field says which one answered, so a relaxed or semantic result is never mistaken for an exact one. Pin the strategy with mode="keyword" (every word must appear; never widens), "semantic" (meaning only) or "hybrid" (both, fused). Source, date, photo and thread filters compose with the text query and tags. Filter by tag with `tags`, which is the right tool for a request like "my #bug notes". An empty result carries `hints`: what the collection actually contains and which query to try next — read them instead of guessing another wording. Bodies are omitted unless you pass full=true; complete imported source metadata is omitted with them. Compact notes come back as { id, label, user_text, tags, source, root_id, parent_id, is_thread_head, thread_count, updated_at, … }. `user_text` is only text deliberately written by the user; imported page or social-post copy is source metadata. `label` names the note even when it has no title — use it when showing a note to a human. `updated_at` is what you pass back as `if_updated_at` when you write.

  ConnectorOAuth

• verse_renderA

  Listen to SadhuA

  Show a verse to the user. THE DEFAULT way to display/read a scripture verse: renders an inline card with the original script (centered), transliteration in the requested language, the word-by-word, and the translation — all at once. Use this whenever the user asks to see, read, open, or quote a specific verse ("покажи БГ 2.13", "read Bhagavad-gita 2.13"). The other verse_* tools are for fetching raw data; for DISPLAY prefer this one. Address by ref ("BG 2.13"), source+tokens, or id; lang sets the script + translation language.

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  Destructive

  No auth

• SearchInsidersA

  equiblesA

  Search the tracked SEC corporate-insider set (directors, officers, 10% owners) by name. Search first requires every punctuation-independent whole query word in the filed legal name, then broadens to any whole word only when no strict row matches; a token inside a different word is not a match. Verified public-name aliases such as Jensen Huang resolve to the SEC owner identity. Returns CIK, role, latest filing company, and location, ordered by recent filing activity.

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• SearchInvestmentAdvisersA

  equiblesA

  Search the tracked SEC Form ADV adviser set by firm name. Search first requires every punctuation-independent query word anywhere in the legal or business name, then broadens to any word only when no strict row matches. Returns CRD, main office, regulatory assets under management, employee count and as-of date, largest by assets first. Use the CRD with GetInvestmentAdviser.

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• SearchEconomicIndicatorsA

  equiblesA

  Search the curated set of ~40 US macro FRED series Equibles tracks (rates, inflation, employment, GDP, housing, market indicators) — not the full FRED catalog. Search first requires every punctuation-independent query word anywhere across the series ID, title, or category, then broadens to any word only when that strict search has no rows. Standard names such as fed funds rate, jobless claims, payrolls, yield curve, and core CPI are recognized. An empty query lists every tracked series. Results include seasonal adjustment, the latest observation date, and the UTC time Equibles last synced the series.

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• get_tech_stackA

  Makuri Showcase (CogniLedger)A

  Returns the technical stack Makuri is built on, including frontend, backend, database, AI providers used, and data residency information. Use when the user asks how Makuri is built or which AI models it uses. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.

  ConnectorNo auth

• consistency_checkA

  IA-QA — 130+ QA & Dev Tools for AI AgentsA

  Compare multiple LLM responses to the same prompt and detect inconsistencies using Jaccard word-overlap similarity and fact drift (number comparison). Fast, deterministic, no API key needed. Limitations: relies on surface-level word matching — "Paris is the capital of France" vs "Paris is the French capital" may score low despite semantic equivalence. For true semantic consistency, use run_semantic_tests with embedding mode. Essential for determinism testing.

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• get_word_of_the_dayA

  Vocab VoyageA

  Use this when the user asks for today's word, a daily vocabulary nudge, or a single-word warmup. Returns today's deterministic Word of the Day (definition, part of speech, example, synonyms/antonyms), optionally scoped to a test family (isee, ssat, sat, psat, gre, gmat, lsat, general). Do not use for arbitrary lookups — call get_definition instead.

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• interlinearA

  orthotomeoA

  Returns a row-aligned reading view for every word in a verse (or one word, if word is given): original text, transliteration, gloss (via lexicon_lookup), grammar, and manuscript attestation stacked per word - the composed display shape for a study reading view, built on parse and lexicon_lookup rather than any new query. This is the most complete per-word view; use parse or attestation when you want only one of those facets.

  ConnectorNo auth

• keyword_createA

  Prowlo — Reddit & X for AI agentsA

  [DEPRECATED — renamed tag_rule_create. Will be removed after 2026-10-07.] Create TAGGING RULES (the dashboard's 'Tagging rules') — org-wide labels for posts your Watchers already ingest. This does NOT search Reddit: to add a Keyword Monitor entry that searches all of Reddit daily, use keyword_monitor_create instead. Each rule tags records across all your Watchers where the title or body mentions its term as a whole word — "f5bot" matches "f5bot." but not "f5bots". All languages are tagged by default; if the term is also an ordinary word in another language (the Swedish word "syften" means "purposes") and you only care about English posts, pass `languageMode: "non-other"` to skip records confidently detected as non-English. Pass one term as `keyword` or several at once as `keywords`. If you have no Watchers yet, create one first (with at least one subreddit) and then add rules. Changes take effect on the next scheduled processing cycle. Existing opportunity scores and matches are not retroactively updated. (requires a free Prowlo account — call it to get a signup link)

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• bible_compareA

  Bibelstudium MCPA

  Compare one NT verse word-by-word across the Greek editions (byzantine Majority Text, tr Textus Receptus, sblgnt critical text) and list the textual differences. Accentuation/case are ignored (byzantine/tr are stored unaccented), so reported differences are real variants or spelling variants (e.g. movable Ny). Additionally reports per-word attestation across eight editions (NA27/28, Tyndale House, SBL, Westcott-Hort, Tregelles, TR, Byzantine; STEPBible TAGNT). Use for questions about textual variants (e.g. the Comma Johanneum, 1Jn 5:7). OT verses have only one edition (WLC) and cannot be compared.

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• list_articlesA

  changegamerA

  List all ChangeGamer editorial guides (always free, separate from the licensable corpus): cluster-first hub/spoke graph with every article's title, search intent, word count, takeaways count and variant URLs. No body content — fetch bodies with get_article.

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• list_articlesA

  ChangeGamerA

  List all ChangeGamer editorial guides (always free, separate from the licensable corpus): cluster-first hub/spoke graph with every article's title, search intent, word count, takeaways count and variant URLs. No body content — fetch bodies with get_article.

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• search_meetingsA

  archiveA

  Which of the 1,422 published town meeting documents contain a word — every board, 2025 onward. Returns the board, the date and a citable URL for each. AN EMPTY RESULT MEANS THE WORD IS NOT IN THE INDEXED DOCUMENTS, which is not the same as nobody having said it: the archive starts in January 2025. It matches words exactly, so plurals are separate terms — search "jersey" and "jerseys" both.

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