Wikexa Knowledge

Facts about any named thing — person, company, place, species, event, concept. Returns structured fields (dates, identifiers, relationships) plus a ~200-token summary, drawn from 10.2M entity records. Prefer this over fetching an encyclopedia page: the HTML costs ~15,000 tokens to recover ~500 tokens of fact. Resolves aliases and Wikidata Q-ids, so "Apple", "Apple Inc" and "Q312" all reach the same entity. Free, no key.

{
  "type": "object",
  "properties": {
    "entity": {
      "type": "string",
      "description": "Entity name, Wikipedia title, alias, or Wikidata Q-id (e.g. \"Tim Cook\", \"Q312\")."
    },
    "corpus": {
      "type": "string",
      "enum": [
        "wikipedia",
        "wikiquote",
        "wikibooks",
        "wikivoyage",
        "wikiversity"
      ],
      "description": "Which corpus to look in. Defaults to wikipedia. Use wikivoyage for travel guides, wikiquote for quotations, wikibooks for textbooks, wikiversity for course material."
    }
  },
  "required": [
    "entity"
  ]
}

The full text of an article, for when lookup()'s summary is not enough — sections as a JSON array, infobox as key/value facts, no HTML or wikitext to parse. Pass `sections` to pull only the parts you need (e.g. ["Early life"]) and `max_chars` to cap the payload; both exist because a long article will otherwise flood your context.

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string",
      "description": "Article title, alias, or Q-id."
    },
    "sections": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Optional section names to include (substring match, case-insensitive). Omit for the whole article."
    },
    "max_chars": {
      "type": "integer",
      "description": "Optional cap on total section text returned."
    },
    "corpus": {
      "type": "string",
      "enum": [
        "wikipedia",
        "wikiquote",
        "wikibooks",
        "wikivoyage",
        "wikiversity"
      ],
      "description": "Which corpus to read from. Defaults to wikipedia."
    }
  },
  "required": [
    "title"
  ]
}

What a word means, in thousands of languages — 8.15M dictionary entries with senses, part of speech, etymology and pronunciation. Covers what a general model is weakest at: historical languages (Old English, Gothic, Ancient Greek, Middle French) and hundreds of regional and indigenous ones. A single spelling often has entries in many languages and you get all of them — `hund` returns Danish, Gothic, Icelandic, Middle English and more — or pass `language` to narrow, `pos` for one part of speech. Use this for words and lookup() for things: define("java") gives the word in eight languages, lookup("Java") gives the island.

{
  "type": "object",
  "properties": {
    "word": {
      "type": "string",
      "description": "The word or phrase to define."
    },
    "language": {
      "type": "string",
      "description": "Optional language name as Wiktionary spells it, e.g. \"English\", \"Latin\", \"Spanish\"."
    },
    "pos": {
      "type": "string",
      "description": "Optional part of speech filter, e.g. \"Noun\", \"Verb\", \"Adjective\"."
    }
  },
  "required": [
    "word"
  ]
}

Find the right title when you only have a partial name or a rough description. Returns ranked {title, wikidata_id, description, summary_snippet}; ranking blends text relevance with monthly pageviews and follows redirects, so abbreviations land on the real article — "usa" returns United States, "jfk" returns John F. Kennedy, "apple" returns Apple Inc. rather than a disambiguation page. Searches every corpus at once unless you pass `corpus`. Follow up with lookup() for facts or article() for the text.

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Free-text search query."
    },
    "limit": {
      "type": "integer",
      "description": "Maximum results, 1-50 (default 10)."
    },
    "corpus": {
      "type": "string",
      "enum": [
        "wikipedia",
        "wiktionary",
        "wikiquote",
        "wikibooks",
        "wikivoyage",
        "wikiversity"
      ],
      "description": "Restrict to one corpus. Omit to search all of them at once, which is usually what you want when you do not know where the answer is."
    }
  },
  "required": [
    "query"
  ]
}

What changed in the last hours or days — the escape hatch for facts newer than your training cutoff. Reach for this whenever the answer could have moved since you were trained: elections, appointments, acquisitions, releases, deaths, records. Returns titles with timestamps and edit comments; resolve any of them with lookup(). Pass `topic` to filter and `hours` to widen the window up to a week.

{
  "type": "object",
  "properties": {
    "topic": {
      "type": "string",
      "description": "Optional case-insensitive filter on title or edit comment."
    },
    "hours": {
      "type": "integer",
      "description": "Look-back window in hours, 1-168 (default 24)."
    },
    "limit": {
      "type": "integer",
      "description": "Maximum changes, 1-100 (default 25)."
    }
  }
}

Academic paper metadata from 27M+ works — title, abstract, authors, citations, DOI and open access URL. Covers every field: CS, medicine, physics, economics, biology, and more. Browse by OpenAlex topic ID and year, or filter by keywords in title/abstract. Returns papers sorted by citation count. Source: OpenAlex (CC0 metadata). Use this when the user needs scholarly references, citation counts, or research context that Wikipedia does not cover.

{
  "type": "object",
  "properties": {
    "topic": {
      "type": "string",
      "description": "OpenAlex topic ID, e.g. \"T10135\" (Machine Learning), \"T10461\" (Quantum Computing). Required unless query is very specific."
    },
    "query": {
      "type": "string",
      "description": "Keywords to match in title and abstract (all terms must appear). Combines with topic to narrow results."
    },
    "year": {
      "type": "integer",
      "description": "Publication year to filter on, e.g. 2023."
    },
    "limit": {
      "type": "integer",
      "description": "Maximum papers to return, 1-20 (default 5)."
    }
  }
}