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Evidence row 545740

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint 47dc2c53-3cae-4a75-aa4e-60c1511e5f3d
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
5ac3fc06e15d1aab3200b4eb13f0340b4ab27310e97dc02d855ca7a66e9bf79a
Leaf
0xbedf3fa283efc5d6aaaef3b46fd0ad74768c1df3b02206131cacb4fd8d5ed55e

What was observed

{
  "count": 6,
  "tools": [
    {
      "description": "Open roles at AI companies, searchable by keyword, company, function (Engineering, Product, Sales, AI & Data, ...) and place (city, country or Remote).",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "company": {
            "description": "Company slug or exact name.",
            "type": "string"
          },
          "cursor": {
            "description": "Pass next_cursor from the previous result to get the next page.",
            "type": "string"
          },
          "limit": {
            "default": 10,
            "description": "Results to return, 1 to 25.",
            "maximum": 25,
            "minimum": 1,
            "type": "integer"
          },
          "place": {
            "description": "City, country or Remote.",
            "type": "string"
          },
          "query": {
            "type": "string"
          },
          "role": {
            "description": "Function, e.g. Engineering.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "find_ai_jobs"
    },
    {
      "description": "Full public profile of one company by slug (from search_ai_companies): description, founders, funding facts, open roles, recent news and source links.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "slug": {
            "description": "Company slug, e.g. 'act.security'.",
            "type": "string"
          }
        },
        "required": [
          "slug"
        ],
        "type": "object"
      },
      "name": "get_company"
    },
    {
      "description": "Dated, source-linked AI news events, newest first, optionally filtered by keyword or company. Each item links to the primary source and to our article.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "cursor": {
            "description": "Pass next_cursor from the previous result to get the next page.",
            "type": "string"
          },
          "limit": {
            "default": 10,
            "description": "Results to return, 1 to 20.",
            "maximum": 20,
            "minimum": 1,
            "type": "integer"
          },
          "query": {
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "latest_ai_news"
    },
    {
      "description": "The sectors and countries that can be used as filters, with company counts. Call this first if unsure how a sector or country is spelled.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "kind": {
            "default": "both",
            "enum": [
              "both",
              "sectors",
              "countries"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_sectors_countries"
    },
    {
      "description": "Find AI startups and companies by topic, sector, country, funding stage, founding year or whether they are hiring. Example: query 'clinical documentation', country 'Australia'. Returns name, one-liner, sector, country, funding facts, website and the presentofai.com page to cite.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "country": {
            "description": "A country name, e.g. 'Germany'.",
            "type": "string"
          },
          "cursor": {
            "description": "Pass next_cursor from the previous result to get the next page.",
            "type": "string"
          },
          "founded": {
            "description": "A year (2023) or a range (2021-2024).",
            "type": "string"
          },
          "hiring_only": {
            "description": "Only companies with open roles.",
            "type": "boolean"
          },
          "limit": {
            "default": 10,
            "description": "Results to return, 1 to 25.",
            "maximum": 25,
            "minimum": 1,
            "type": "integer"
          },
          "query": {
            "description": "Words about what the company does, e.g. 'voice agents', 'legal contracts'.",
            "type": "string"
          },
          "sector": {
            "description": "A sector name; see list_sectors_countries.",
            "type": "string"
          },
          "stage": {
            "enum": [
              "pre-seed",
              "seed",
              "series-a",
              "series-b",
              "series-c",
              "series-d"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "search_ai_companies"
    },
    {
      "description": "Topics currently trending across AI companies we track (with example companies and latest news) and the companies hiring the most.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "whats_trending"
    }
  ]
}

What the leaf hashes

{"body":"5ac3fc06e15d1aab3200b4eb13f0340b4ab27310e97dc02d855ca7a66e9bf79a","id":545740,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793132628777585,"prev":null,"subject":"47dc2c53-3cae-4a75-aa4e-60c1511e5f3d","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (273461 rows).

  1. 0xbedf1df52c04e11b49421718027bde738937b85c1e26d3b4e6e1590576ae3079
  2. 0x74aadbd63fe1de908ac40489828e5a9669fa96ab26446fd3da1e225725ee1c86
  3. 0x42db153640a48aa8402ff58233b973006388a6c9d2c7ade71ce01343feac472b
  4. 0xa5394c516761161f665297b70152bee2e5d360a5ab6f52e719f750609878b3e4
  5. 0xc2fee796c3ba0f17c5300d08faa6ddcc89b61ed9c40f1b2c99bf092ae6aea807
  6. 0x5c15596cf3ae3b91f864fe742e571b2fc0aff67ff907e2c0c3f177fb63e9030c
  7. 0x58076513bb577ca8a53dd885b07515e0ece5737afd15f2ece1bf1c51c23a87e7
  8. 0x0212cd662309a7d2d129f9a67d2f66663abb099b98ea07f2ecee5ef0015b9020
  9. 0x5231e4891ad923b3f258099e075d324f038dc0f231f0be80f0053aed6cd321a2
  10. 0x07d94d6cad25c6ae0e779d2360b8ba5cd8b7de174c7725cc85c5f657520ce9d5
  11. 0xd56d79fc64fcae6a2e1352c41b43956079c13a181e210c5add0c9bcf961987ef
  12. 0xa9bcdb8be937595e637058d98ed979d02cbac590262daa97def86c50ca63628b
  13. 0xb4800af1fe2ae822adba5c087faf1dc0bc2d7c9de2e3e602a2b65aefc1d53c94
  14. 0xa453d1738637a5c663802d07ce095aa340c80d53a4288ae277a72e265868ce4e
  15. 0x73341bb09dd901ca47f26173883431496e3d98d6b0fb5b89f36218126d46c5d4
  16. 0xa94627de1af0e823832e05a9069b304ecccb8c0cdb8f9cfc4f2039bfb9799dc5
  17. 0xdf1105afdc109de3c09a98fc8a3864159ad964e6f49b635c105a27a1e1f14310
  18. 0x2bf8151e5f157dd183b9de6fa00469551932a7a6e3f33a694895000ac9061197
  19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
Day root
0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
Chained
0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
Published
On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4

How to check it · This row as JSON