Evidence row 38125

What was observed

{
  "endpoints": [
    [
      "mcp",
      "https://hpsilab.com/mcp"
    ],
    [
      "web",
      "https://hpsilab.com/"
    ]
  ],
  "name": "HPSILab Quant Finance",
  "owner_address": null,
  "raw": {
    "_meta": {
      "io.modelcontextprotocol.registry/official": {
        "isLatest": true,
        "publishedAt": "2026-10-24T11:26:12.287559Z",
        "status": "active",
        "statusChangedAt": "2026-10-24T11:26:12.287559Z",
        "updatedAt": "2026-10-24T11:26:12.287559Z"
      }
    },
    "server": {
      "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
      "description": "Stock & options risk analytics for AI agents: pre-trade risk scan, IV, gamma walls, Monte Carlo.",
      "name": "io.github.haiyunsky/hpsilab-quant-finance-mcp",
      "packages": [
        {
          "environmentVariables": [
            {
              "description": "HPSILab API key generated and managed in HPSILab Settings.",
              "format": "string",
              "isRequired": true,
              "isSecret": true,
              "name": "HPSILAB_API_KEY"
            }
          ],
          "identifier": "hpsilab-quant-finance-mcp",
          "registryBaseUrl": "https://pypi.org",
          "registryType": "pypi",
          "runtimeHint": "uvx",
          "transport": {
            "type": "stdio"
          },
          "version": "0.11.1"
        }
      ],
      "remotes": [
        {
          "headers": [
            {
              "description": "Optional. Clients that support MCP OAuth can omit it and sign in to HPSILab instead; otherwise send a Bearer API key from HPSILab Settings. Research tools need one of the two.",
              "isSecret": true,
              "name": "Authorization"
            }
          ],
          "type": "streamable-http",
          "url": "https://hpsilab.com/mcp"
        }
      ],
      "repository": {
        "source": "github",
        "url": "https://github.com/haiyunsky/hpsilab-quant-finance-mcp"
      },
      "title": "HPSILab Quant Finance",
      "version": "0.11.1",
      "websiteUrl": "https://hpsilab.com"
    }
  },
  "source": "mcp_registry",
  "summary": "Stock & options risk analytics for AI agents: pre-trade risk scan, IV, gamma walls, Monte Carlo."
}

What the leaf hashes

{"body":"01d8b50d752c1fa6bd59564225ede5d1007ebc34ff3a1d7e8eb31d3806380c8b","id":38125,"kind":"listing","method":"baseline/1","observed_us":1793025391478807,"prev":null,"subject":"mcp_registry:io.github.haiyunsky/hpsilab-quant-finance-mcp","subject_kind":"source_record"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-26 (296695 rows).

1. 0xe40aa8dba9ee483f20e0a94bb9edee7aa296518ca387a7f2fb2719f14d765dc0
2. 0xd51749a6d2f3c7525936857807fe9eb5960826b8e5ac4813696ce793ba50a225
3. 0x14a02207db2d950ebcaec65a9b2862c5b758a73f68ac99fdc39a52536eb1639e
4. 0x88572b137acbcf0437491d7d6c9a100caf7f45e40acacc4953a935ab0375145f
5. 0xc35b62ff3f8797ef8d73b9269eba0893d25fa22e8b0236c1cc6ca1365f5fd943
6. 0xfedf8c18c113f007bff4908d58bef862c70b2e9d5617c620e3be25f3c0e42e75
7. 0xd7723874e8aef7e89ea8b6764032b4383b5490bf178fa901de9d697a63a4a320
8. 0xef83bea5e8b70f345bff72e370234bbbe5a17ab662cbc06ac11ca3543f4eeb03
9. 0x444a7376940e2830bf72adff90bc8741426d1d746343c45469f2b29d6ccebab3
10. 0x15726dc36d12291b4937cc1d22f325d4939ad46dd10d4e44468a88a8cc8329ed
11. 0x162e0da99198c9cdc9c43bf4626e85f4a7092fdb31ea15c7126e1f98b20eaa56
12. 0x2fc38b57208d692aab1ee89b6e26917df292126314027c27360c5644a63fd0bc
13. 0xc0924a0807e534382f518663123231c317124338831a2b310de2c17b09677086
14. 0x9bc5fc98278b9f6dc18c66c6e162aefd5244be03170d41bc5161f58ad11beed7
15. 0x95657a7d540ed6cac0bde9995782333b2562a9a6641853269ac95148827410f0
16. 0x5fb5dda563336cd1bc1b9f44c52b76237ae72ed2145cb9290f39f304ca7dd678
17. 0x74a0a08e4e7ab9aa5bfbead33dec7e1c7e8e364cff69a63720d764bbe987aadc

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae