Server definition

Hash: sha256:22067016edd56a38a79a250bd72a4cbbe57dccce114b2f13dde80015fafce759
What it is: What a remote MCP server returned when asked what it offers: 6 tools

The blob, as servednamed by its sha256

{
  "instructions": "Structured knowledge for agents, from Wikipedia, Wikidata, Wiktionary, Wikiquote, Wikibooks, Wikivoyage, Wikiversity, and OpenAlex. lookup(entity) for facts and a short summary, article(title) for full structured text, define(word) for dictionary senses, search(query) when the exact title is unknown, recent(topic) for changes newer than your training cutoff, papers(topic, query) for academic paper metadata from 27M+ works. lookup, article and search take an optional `corpus`; search spans all corpora when you omit it. Everything is free. Text is CC BY-SA 4.0 — keep the source_url when you quote it. Paper metadata is CC0.",
  "tools": [
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "corpus": {
            "description": "Which corpus to read from. Defaults to wikipedia.",
            "enum": [
              "wikipedia",
              "wikiquote",
              "wikibooks",
              "wikivoyage",
              "wikiversity"
            ],
            "type": "string"
          },
          "max_chars": {
            "description": "Optional cap on total section text returned.",
            "type": "integer"
          },
          "sections": {
            "description": "Optional section names to include (substring match, case-insensitive). Omit for the whole article.",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "title": {
            "description": "Article title, alias, or Q-id.",
            "type": "string"
          }
        },
        "required": [
          "title"
        ],
        "type": "object"
      },
      "name": "article",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "language": {
            "description": "Optional language name as Wiktionary spells it, e.g. \"English\", \"Latin\", \"Spanish\".",
            "type": "string"
          },
          "pos": {
            "description": "Optional part of speech filter, e.g. \"Noun\", \"Verb\", \"Adjective\".",
            "type": "string"
          },
          "word": {
            "description": "The word or phrase to define.",
            "type": "string"
          }
        },
        "required": [
          "word"
        ],
        "type": "object"
      },
      "name": "define",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "corpus": {
            "description": "Which corpus to look in. Defaults to wikipedia. Use wikivoyage for travel guides, wikiquote for quotations, wikibooks for textbooks, wikiversity for course material.",
            "enum": [
              "wikipedia",
              "wikiquote",
              "wikibooks",
              "wikivoyage",
              "wikiversity"
            ],
            "type": "string"
          },
          "entity": {
            "description": "Entity name, Wikipedia title, alias, or Wikidata Q-id (e.g. \"Tim Cook\", \"Q312\").",
            "type": "string"
          }
        },
        "required": [
          "entity"
        ],
        "type": "object"
      },
      "name": "lookup",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "limit": {
            "description": "Maximum papers to return, 1-20 (default 5).",
            "type": "integer"
          },
          "query": {
            "description": "Keywords to match in title and abstract (all terms must appear). Combines with topic to narrow results.",
            "type": "string"
          },
          "topic": {
            "description": "OpenAlex topic ID, e.g. \"T10135\" (Machine Learning), \"T10461\" (Quantum Computing). Required unless query is very specific.",
            "type": "string"
          },
          "year": {
            "description": "Publication year to filter on, e.g. 2023.",
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "papers",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "hours": {
            "description": "Look-back window in hours, 1-168 (default 24).",
            "type": "integer"
          },
          "limit": {
            "description": "Maximum changes, 1-100 (default 25).",
            "type": "integer"
          },
          "topic": {
            "description": "Optional case-insensitive filter on title or edit comment.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "recent",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "corpus": {
            "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.",
            "enum": [
              "wikipedia",
              "wiktionary",
              "wikiquote",
              "wikibooks",
              "wikivoyage",
              "wikiversity"
            ],
            "type": "string"
          },
          "limit": {
            "description": "Maximum results, 1-50 (default 10).",
            "type": "integer"
          },
          "query": {
            "description": "Free-text search query.",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search",
      "outputSchema": null
    }
  ]
}

Verify it yourself

curl -s https://api.teppi.xyz/v1/evidence/sha256:22067016edd56a38a79a250bd72a4cbbe57dccce114b2f13dde80015fafce759 | sha256sum