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222,451 tools. Last updated 2026-06-21 18:41

"Exploring the word 'Make' and its possible applications" matching MCP tools:

  • Make a saved thesis discoverable by flipping its visibility: `public` (default) surfaces it on the author's /[handle] profile and counts toward their reputation aggregate; `unlisted` makes it reachable at a known direct link but keeps it off the profile. Use AFTER save_thesis to promote an existing thesis (save_thesis sets visibility only at creation). Idempotent. Pair with unpublish_thesis to revert to private. Tier: sp500+ (sample rejected).
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  • Discover the fleet's deeper machinery. No args → every mounted domain with its verbs grouped by rung (lookup → composability → contested → frontier). With `domain` → that domain's full tool list with descriptions and input schemas. Invoke anything it lists via `call`. Use this whenever the spine (lookup/search/verify) is too shallow for the question — e.g. "what can I make/patch/cover with MY inventory", contested claims, open questions.
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  • Make a saved claim discoverable by flipping its visibility: `public` (default) surfaces it on the author's /[handle] profile and counts toward their claim-accuracy reputation; `unlisted` makes it reachable at a known direct link but keeps it off the profile. Use AFTER save_claim to promote an existing claim. Idempotent. Pair with unpublish_claim to revert to private. Tier: sp500+ (sample rejected).
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  • List applications across all accessible jobs. Supports filtering by candidate, job, stage, status, AI score range, and date ranges. Use for pipeline analytics, sync jobs, and ATS dashboards. Avoid include=candidate or include=cv.text on large pages (each embeds heavy nested data); if the response exceeds the budget the tool returns isError:true with error_code=response_too_large and retry hints. Each application embeds its current `stage` (IdName) directly in the response — this is sufficient for rendering kanban/pipeline views; you DO NOT need to call hires_get_job to fetch workflow_stages separately when rendering a pipeline.
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  • Search the bundled OurAirports corpus by free-text (name / municipality / keywords) and/or facets (country, region, type). Every query token must match (word order and partial words are handled). Returns ranked airport summaries — operational and larger airports first — each with its full code set and coordinates, ready to chain into ourairports_get_airport. Closed airports are excluded unless include_closed is set. Use ourairports_list_countries for valid country/region codes. For "nearest airport to a coordinate" use ourairports_find_airports instead. OurAirports is community-edited — not authoritative for flight operations.
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  • Poll the current status of a token deployment by its intentId. Use this after ava_deploy_token times out, or to check progress of an ava_create_token_intent flow. Returns: status ('deploying' | 'deployed' | 'failed'), contractAddress and explorer links when deployed, errorMessage on failure. Poll every 5-10 seconds. Most deployments complete within 60 seconds. Possible errors: insufficient fee sent, gas spike, RPC timeout — check errorMessage field.
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  • Poll the current status of a token deployment by its intentId. Use this after ava_deploy_token times out, or to check progress of an ava_create_token_intent flow. Returns: status ('deploying' | 'deployed' | 'failed'), contractAddress and explorer links when deployed, errorMessage on failure. Poll every 5-10 seconds. Most deployments complete within 60 seconds. Possible errors: insufficient fee sent, gas spike, RPC timeout — check errorMessage field.
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  • Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.
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  • Look a Proto-Scythian lemma up on Wiktionary and return its senses plus its full descendants payload — the reconstructed etymology and the reflex tree down to Ossetian and Khotanese, attested scholarship, not invention. Plain ASCII spellings are folded to the reconstruction's diacritics and the result notes the resolution. With search_language='eng' the query is an English word instead: the result lists the lemmas whose glosses match it (the translations block) plus their expanded entries. Returns Markdown plus the same result as structuredContent matching the declared outputSchema. Results are cached server-side; first-time queries reach the live upstream politely and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Content is from en.wiktionary.org (CC BY-SA 4.0 — attribute and share alike if republished).
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  • Given the ingredients you have on hand, find every cocktail you can make completely — one where you already have all of its ingredients. Garnishes are treated as optional and plain water is assumed available; soda and tonic water are not. Matching is word-based, not substring: "gin" matches "London dry gin" but not "ginger beer", and generic terms do not match product-class extras ("gin" will not cover "sloe gin" or "orange bitters"). Returns two lists: "makeable" (drinks you can make now, up to 60) and "almostMakeable" (drinks exactly one ingredient short, up to 25, each naming the missing ingredient). Drinks needing two or more extra ingredients are omitted entirely. Both lists are ordered simplest first — fewest distinct ingredients in the full recipe, then alphabetical by name. Use this for multi-ingredient "what can I make?" questions; for a single ingredient use find_cocktails_by_ingredient.
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  • Get a complete overview of all senses for a Danish word in a single call. Replaces the common pattern of calling get_word_synsets → get_synset_info per result → get_word_synonyms, collapsing 5-15 HTTP round-trips into one SPARQL query. Only returns synsets where the word is a primary lexical member (i.e. the word itself has a direct sense in the synset), excluding multi-word expressions that merely contain the word as a component. Args: word: The Danish word to look up Returns: List of dicts, one per synset, each containing: - synset_id: Clean synset identifier (e.g. "synset-3047") - label: Human-readable synset label - definition: Synset definition (may be truncated with "…") - ontological_types: List of dnc: type URIs - synonyms: List of co-member lemmas (true synonyms only) - hypernym: Dict with synset_id and label of the immediate broader concept, or null - lexfile: WordNet lexicographer file name (e.g. "noun.animal"), or null if absent Example: overview = get_word_overview("hund") # Returns list of 4 synsets, the first being: # {"synset_id": "synset-3047", # "label": "{hund_1§1; køter_§1; vovhund_§1; vovse_§1}", # "definition": "pattedyr som har god lugtesans ...", # "ontological_types": ["dnc:Animal", "dnc:Object"], # "synonyms": ["køter", "vovhund", "vovse"], # "lexfile": "noun.animal"} # Pass synset_id to get_synset_info() for full JSON-LD data on any result: # full_data = get_synset_info(overview[0]["synset_id"])
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  • Fetch one Federal Register document by its FR document number — full metadata (title, type, agencies, abstract, action, effective/comment dates, RINs) plus the cross-source handles that make this a workflow server. The output carries the docket ID (chain into regulations_get_docket or regulations_find_comments) and the affected CFR parts (chain into regulations_get_cfr_section). Set include_full_text only when the rule body itself is needed — final rules can run tens of thousands of words.
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  • Look a Proto-Scythian lemma up on Wiktionary and return its senses plus its full descendants payload — the reconstructed etymology and the reflex tree down to Ossetian and Khotanese, attested scholarship, not invention. Plain ASCII spellings are folded to the reconstruction's diacritics and the result notes the resolution. With search_language='eng' the query is an English word instead: the result lists the lemmas whose glosses match it (the translations block) plus their expanded entries. Returns Markdown plus the same result as structuredContent matching the declared outputSchema. Results are cached server-side; first-time queries reach the live upstream politely and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Content is from en.wiktionary.org (CC BY-SA 4.0 — attribute and share alike if republished).
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  • Look an Old Norse word up on Wiktionary and return its senses plus full declension/conjugation tables — attested content (including the verbs' mediopassive voice), not invented. Any form of the word works; an inflected query is resolved to its lemma automatically via previously cached paradigms and the result notes the resolution. With search_language='eng' the query is an English word instead: the result lists its per-sense Old Norse equivalents (the translations block) plus their expanded entries. Returns Markdown plus the same result as structuredContent matching the declared outputSchema. Results are cached server-side; first-time queries reach the live upstream politely and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Content is from en.wiktionary.org (CC BY-SA 4.0 — attribute and share alike if republished).
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  • Look a word up in the real Livonian–Estonian–Latvian dictionary and return only attested content, so translations are grounded, not invented. Search a meaning (in English/Latvian/Estonian) to find the Livonian headword, or a Livonian word to confirm it exists and read its sense, part of speech and examples. See the `query` and `search_language` parameter docs for how to phrase a query. By default each match's full inflection table is returned inline, so one call usually suffices; on a broad query only the first N tables expand (the rest are listed as handles to fetch with get_inflections). Returns Markdown plus the same result as structuredContent matching the declared outputSchema. Results are cached server-side, so repeating a query is instant and free; a first-time query reaches the live dictionary and calls are rate limited — on a rate-limit error, wait a few seconds and retry instead of re-issuing immediately. Dictionary content is from livonian.tech (CC BY-SA 4.0 — attribute if republished).
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  • Search the Jisho.org Japanese<->English dictionary. The keyword can be English (translate to Japanese), Japanese kanji/kana, or romaji. Returns up to `limit` matching dictionary entries, each with the headword (slug), whether it is a common word, JLPT level, all readings/spellings, and English meanings grouped into senses with parts of speech. Use this to translate, look up a kanji/kana word, or find Japanese words for an English concept.
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  • Look an Old Church Slavonic word up on Wiktionary and return its senses plus full declension/conjugation tables — attested content (singular, dual and plural), not invented. Any form of the word works; an inflected query is resolved to its lemma automatically via previously cached paradigms and the result notes the resolution. With search_language='eng' the query is an English word instead: the result lists its per-sense Old Church Slavonic equivalents (the translations block) plus their expanded entries. Returns Markdown plus the same result as structuredContent matching the declared outputSchema. Results are cached server-side; first-time queries reach the live upstream politely and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Content is from en.wiktionary.org (CC BY-SA 4.0 — attribute and share alike if republished).
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  • Get synsets (word meanings) for a Danish word, returning a sorted list of lexical concepts. DanNet follows the OntoLex-Lemon model where: - Words (ontolex:LexicalEntry) evoke concepts through senses - Synsets (ontolex:LexicalConcept) represent units of meaning - Multiple words can share the same synset (synonyms) - One word can have multiple synsets (polysemy) This function returns all synsets associated with a word, effectively giving you all the different meanings/senses that word can have. Each synset represents a distinct semantic concept with its own definition and semantic relationships. Common patterns in Danish: - Nouns often have multiple senses (e.g., "kage" = cake/lump) - Verbs distinguish motion vs. state (e.g., "løbe" = run/flow) - Check synset's dns:ontologicalType for semantic classification DDO CONNECTION AND SYNSET LABELS: Synset labels are compositions of DDO-derived sense labels, showing all words that express the same meaning. For example: - "{hund_1§1; køter_§1; vovhund_§1; vovse_§1}" = all words meaning "domestic dog" - "{forlygte_§2; babs_§1; bryst_§2; patte_1§1a}" = all words meaning "female breast" Each individual sense label follows DDO structure: - "hund_1§1" = word "hund", entry 1, definition 1 in DDO (ordnet.dk) - "patte_1§1a" = word "patte", entry 1, definition 1, subdefinition a - The § notation connects directly to DDO's definition numbering system This composition reveals the semantic relationships between Danish words and their shared meanings, all traceable back to authoritative DDO lexicographic data. RETURN BEHAVIOR: This function has two possible return modes depending on search results: 1. MULTIPLE RESULTS: Returns List[SearchResult] with basic information for each synset 2. SINGLE RESULT (redirect): Returns full synset data Dict when DanNet automatically redirects to a single synset. This provides immediate access to all semantic relationships, ontological types, sentiment data, and other rich information without requiring a separate get_synset_info() call. The single-result case is equivalent to calling get_synset_info() on the synset, providing the same comprehensive RDF data structure with all semantic relations. Args: query: The Danish word or phrase to search for language: Language for labels and definitions in results (default: "da" for Danish, "en" for English when available) Note: Only Danish words can be searched regardless of this parameter Returns: MULTIPLE RESULTS: List of SearchResult objects with: - word: The lexical form - synset_id: Unique synset identifier (format: synset-NNNNN) - label: Human-readable synset label (e.g., "{kage_1§1}") - definition: Brief semantic definition (may be truncated with "...") SINGLE RESULT: Dict with complete synset data including: - All RDF properties with namespace prefixes (e.g., wn:hypernym) - dns:ontologicalType → semantic types with @set array - dns:sentiment → parsed sentiment (if present) - synset_id → clean identifier for convenience - All semantic relationships and linguistic properties Examples: # Multiple results case results = get_word_synsets("hund") # Returns list of search result dictionaries for all meanings of "hund" # => [{"word": "hund", "synset_id": "synset-3047", ...}, ...] # Single result case (redirect) result = get_word_synsets("svinkeærinde") # Returns complete synset data for unique word # => {'wn:hypernym': 'dn:synset-11677', 'dns:sentiment': {...}, ...}
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  • Look an Old Norse word up on Wiktionary and return its senses plus full declension/conjugation tables — attested content (including the verbs' mediopassive voice), not invented. Any form of the word works; an inflected query is resolved to its lemma automatically via previously cached paradigms and the result notes the resolution. With search_language='eng' the query is an English word instead: the result lists its per-sense Old Norse equivalents (the translations block) plus their expanded entries. Returns Markdown plus the same result as structuredContent matching the declared outputSchema. Results are cached server-side; first-time queries reach the live upstream politely and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Content is from en.wiktionary.org (CC BY-SA 4.0 — attribute and share alike if republished).
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  • Strip Pāli inflectional suffixes to find the root form (basic stem). 💡 **Use this tool when:** - You find an inflected Pāli word (e.g. `dukkhassa`, `bhikkhūnaṁ`) and `get_word_definition` doesn't find it directly — Pāli inflects nouns across 7 cases × 2 numbers, ~16 forms per root. - You want to split a compound (`sammāsambuddhassa` → `sammā` + `sambuddha` + `-ssa` genitive). - You want to see possible stems before another `get_word_definition` lookup. 🔄 **Recommended workflow:** `parse_pali_word(inflected_form)` → get `possible_stems[]` → call `get_word_definition(stem)` per stem until you find a definition. ⚠️ **Limitations:** - Rule-based first-pass — strips common suffixes (case endings, vowel shortening). Not a full morphological analyzer. - Compound words (samāsa) are NOT split — `dukkhanirodha` won't be broken into `dukkha` + `nirodha`. - Sandhi (sound junctions) like `tena ahaṁ → tenāhaṁ` aren't reversed. - Returns **possible** stems — verify each via `get_word_definition`.
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