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Evidence row 52298

Observed , by baseline/1.

Kind
listing
About
source_record mcp_registry:io.github.skforecast/skforecast-ai
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
431009339142d5ad6e01ca29844e86ac0249d9414d82bcd6ae65fdbbb6255337
Leaf
0xe6f8d4bde8e128c53bec60d20053afb985815fc036285c99e6cdd2d48e60bd02

What was observed

{
  "endpoints": [
    [
      "web",
      "https://ai.skforecast.org/stable/user-guides/mcp-server.html"
    ]
  ],
  "name": "skforecast-ai",
  "owner_address": null,
  "raw": {
    "_meta": {
      "io.modelcontextprotocol.registry/official": {
        "isLatest": true,
        "publishedAt": "2026-10-12T17:23:08.667678Z",
        "status": "active",
        "statusChangedAt": "2026-10-12T17:23:08.667678Z",
        "updatedAt": "2026-10-12T17:23:08.667678Z"
      }
    },
    "server": {
      "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
      "description": "Forecast time series in CSV files: deterministic skforecast workflows and the script that ran.",
      "name": "io.github.skforecast/skforecast-ai",
      "packages": [
        {
          "identifier": "skforecast-ai-mcp",
          "packageArguments": [
            {
              "description": "Absolute path of the directory the server may read CSV files from. Give the narrowest one that holds your data.",
              "format": "filepath",
              "isRequired": true,
              "name": "--allow-dir",
              "type": "named"
            }
          ],
          "registryType": "pypi",
          "runtimeHint": "uvx",
          "transport": {
            "type": "stdio"
          },
          "version": "0.4.2"
        }
      ],
      "repository": {
        "source": "github",
        "url": "https://github.com/skforecast/skforecast-ai"
      },
      "title": "skforecast-ai",
      "version": "0.4.2",
      "websiteUrl": "https://ai.skforecast.org/stable/user-guides/mcp-server.html"
    }
  },
  "source": "mcp_registry",
  "summary": "Forecast time series in CSV files: deterministic skforecast workflows and the script that ran."
}

What the leaf hashes

{"body":"431009339142d5ad6e01ca29844e86ac0249d9414d82bcd6ae65fdbbb6255337","id":52298,"kind":"listing","method":"baseline/1","observed_us":1793025419764586,"prev":null,"subject":"mcp_registry:io.github.skforecast/skforecast-ai","subject_kind":"source_record"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (296695 rows).

  1. 0xe6f84affeb2f284ac2e11ca2371f054ed4a0ce65054e2fc58e236879beb51521
  2. 0x0337b40aea697d5dd1653345f6025da967771bae80bf31bbf4e7208fe5f3f22c
  3. 0xc29d9074fe64f17959356e0e9474c333ad88a9a35c43561fad4bdea8d2433536
  4. 0xde7a2c7c5c6a5b282410cf5ebb57d1d52ccd26854e1bdc1207e0f488c79ed478
  5. 0x65f495bec5820f25d708080e24f94ceafb6e0472f0c083fcefa3a85f5479f40a
  6. 0x4048c8d51c3649199691498469f6a351ed424d301816a1c5dcc1fe397917c278
  7. 0x73bed6e143ef5d37fb42d943e16df242648ea58ba730985b20cc9e0d3326919c
  8. 0x2d079c4f1c7332c64c3e38aecd83cb80e3ba92fa945d7eeb11e1e82b0f92e01b
  9. 0xb095815fc2a9a9dddee3e71a807a7d389d294b6efc360ef8e2c90f32f3a91924
  10. 0x3233c3265058bb5a7e34ed1f4aeeed146adeaf8dd695c350fb002bf738e335da
  11. 0x59e039ae04bb13d1c4f6760e5371456ed0590ed6a27668ea3df8a519b5fd4655
  12. 0xb866b513dd861c870688f5d1a8e434b170eaa2fafb0961d6a674d452b8e58381
  13. 0xafcc1fe54cfe00a3a1de33df127340075f22433bb89848bbc81499cd7aca5b2b
  14. 0x9bc5fc98278b9f6dc18c66c6e162aefd5244be03170d41bc5161f58ad11beed7
  15. 0x95657a7d540ed6cac0bde9995782333b2562a9a6641853269ac95148827410f0
  16. 0x5fb5dda563336cd1bc1b9f44c52b76237ae72ed2145cb9290f39f304ca7dd678
  17. 0x74a0a08e4e7ab9aa5bfbead33dec7e1c7e8e364cff69a63720d764bbe987aadc
Day root
0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8
Chained
0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a
Published
On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae

How to check it · This row as JSON