{"id":301740,"recorded_at":"2026-10-26T22:37:36.231286Z","observed_at":"2026-10-26T22:37:36.231247Z","subject_kind":"endpoint","subject":"bb331bfc-8a9f-4c91-8bb2-0b3ed45e28ae","kind":"mcp.tools","method":"probe.mcp/1","body":{"count":7,"tools":[{"description":"Find all entities of a specific schema.org type (exact type name, for example Service, Person, DefinedTerm).","inputSchema":{"properties":{"type":{"type":"string"}},"required":["type"],"type":"object"},"name":"find_by_type"},{"description":"Find and rank schema.org entities from natural language, tolerating typos and alternative names. Returns bounded entity context with relationship IDs; use get_entity for full detail. The optional detail argument is summary (for each hit: id, type, name, url, the start of the description and the match score) or full (every property and relationship). A client on protocol 2026-07-28 or later gets summary unless it asks for full; an older client gets full unless it asks for summary.","inputSchema":{"properties":{"detail":{"enum":["summary","full"],"type":"string"},"limit":{"default":5,"maximum":10,"minimum":1,"type":"integer"},"query":{"type":"string"},"type":{"type":"string"},"weights":{"properties":{"entityTypes":{"type":"object"},"predicates":{"type":"object"}},"type":"object"}},"required":["query"],"type":"object"},"name":"fuzzy_find_and_traverse"},{"description":"Return passages of the VISEON articles word for word, each with a link to the passage itself, the article it is part of and how much of the query it holds, so an answer can quote and cite them. query: the distinctive words asked about (a name, a term, a phrase the article uses). article: optional, an article's @id, page url or title, to look inside that article only. limit: 1 to 5 passages, default 3. The text is verbatim and unaltered: no model has read or paraphrased it. It matches the article's own words, so ask in the words the article would use; for what the graph says about an article (description, author, date, topics) use fuzzy_find_and_traverse and get_entity.","inputSchema":{"properties":{"article":{"type":"string"},"limit":{"default":3,"maximum":5,"minimum":1,"type":"integer"},"query":{"type":"string"}},"required":["query"],"type":"object"},"name":"get_citable_passages"},{"description":"Get complete schema.org entity data by URL (its @id), including relationships the graph holds in either direction.","inputSchema":{"properties":{"url":{"type":"string"}},"required":["url"],"type":"object"},"name":"get_entity"},{"description":"Find entities connected to a subject: one row per property value, with object_type 'uri' for links to other entities and 'literal' for values. Optionally filter by predicate.","inputSchema":{"properties":{"predicate":{"type":"string"},"subject":{"type":"string"}},"required":["subject"],"type":"object"},"name":"query_relationships"},{"description":"Substring search across the text of every entity; returns up to 20 entity URLs.","inputSchema":{"properties":{"query":{"type":"string"}},"required":["query"],"type":"object"},"name":"search_content"},{"description":"Walk the knowledge graph from one entity in a single call. start: an entity @id or a name (resolved like fuzzy_find_and_traverse). path: one entry per hop, each a predicate or a list of predicates; prefix a predicate with ^ to follow it backwards (e.g. ^worksFor finds who works for an organisation). Literal values (dates, names, emails) named in a hop are returned in values. Example, who founded the company Hamza works for and when: start \"Hamza Ashraf\", path [[\"worksFor\"], [\"founder\", \"foundingDate\"]]. Without path, follows every link for maxHops (1-3, default 2) and returns links only, with a budget of 100 rows shared between hops, so hubs are cut short rather than hiding later hops (use a path to go deeper: a path call may return up to 400 rows). Returns edges [{hop, from, predicate, to, to_name, to_types}], values [{hop, subject, subject_name, predicate, value}], truncated and truncated_hops (the hops that hit a limit).","inputSchema":{"properties":{"maxHops":{"default":2,"maximum":3,"minimum":1,"type":"integer"},"path":{"items":{"anyOf":[{"type":"string"},{"items":{"type":"string"},"type":"array"}]},"maxItems":3,"type":"array"},"start":{"type":"string"}},"required":["start"],"type":"object"},"name":"traverse_path"}]},"body_sha256":"15f6c3eda198fc7478fd29265b0e872c7bcd0a207eacb4370d176e41e6bf23e1","prev_id":null,"leaf":"0x93980c59ca74c2d58434bfb8704ac293e158ef691c1fb6e6172ee90680c2b5a9","leaf_text":"{\"body\":\"15f6c3eda198fc7478fd29265b0e872c7bcd0a207eacb4370d176e41e6bf23e1\",\"id\":301740,\"kind\":\"mcp.tools\",\"method\":\"probe.mcp/1\",\"observed_us\":1793054256231247,\"prev\":null,\"subject\":\"bb331bfc-8a9f-4c91-8bb2-0b3ed45e28ae\",\"subject_kind\":\"endpoint\"}","day":{"day":"2026-10-26","leaves":296695,"root":"0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8","chained":"0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a","anchor_chain":"eip155:5042002","anchor_tx":"0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae","anchor_block":69251483},"proof":["0x93982a32bbc5d55e82005d17bbc256d180d2d776bc42fb3b064f3d98c60ae176","0x8e2a4f1dee5682ad89a887c04466357b9f15c0d228e6512286889aef2630e479","0x5de44251b1cf8698672ca286d9d428a98092d9c3360be2db1b19bfe3edb9d4a4","0x7aae2ddb7b04e330520865e6e9b17b1ad7926e30597dee20dd829b5d3c2a4177","0x3e084844bf0033401626a3e73e4c666955744cf52e2b0c61eee260632ae70781","0xc40f250098dc3fda893360617a2ed0874c93117c8b9c8cdbe903d17a40a2b9ec","0x21ac38178b0900a44217518ff0e1974e4f21bcf978b60ee54a2a96d9455b3e43","0x7a551024620833b5701814d9551a08404cf5e8dfb760c7abf58f3ce06931d1c9","0x9c935e0d4bfff802c2c603de72b42f45c679ee9ab100bb7283c50b183356680c","0x1452bac1c16ed1a13fd24d016370307a5402f74d73cad5641a5508fdb4d2c5cb","0xcd52656344e352446858a7d55feb9336b07dd3ad98715c122aaf69d4eb3d6ca8","0x3b55f6d5345bce3e1332e014f19526d25328fb6283d3518837a015c3621c0d1c","0x45c1d3062bbe98a6b1540c7e2ccf6516eedd6ef07fdfeb1ba77ee6272970447c","0xf0edabbb9ba0d643e5505d19d07637eb6f6aed0a1c7356af43ae7d84ae9ef0c5","0xf0bd63870f0bb378fa300bd33563050dcb7b3e02b44eb3ee550c1c534ec4b246","0x1ac20d30773e1f4f2f811540e9a99b5cca9177c9e2e029acc0d80cf3f1d11f0f","0xd21942ae3214eff88e08ab04884fd4b11958b51af9a0741b7668e2d07a2c56c9","0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f","0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a"]}