netcafe-tables

{
  "id": "aix_cebabe2f16",
  "name": "netcafe-tables",
  "operator": "(unclaimed - source: registry-official · publisher: com.ainetcafe)",
  "description": "Messy spreadsheets in, clean checkable tables out. Every result carries its arithmetic proof.",
  "depth": 1,
  "status": "unclaimed",
  "last_crawled": "2026-08-15",
  "missing_fields": [
    "pricing",
    "reputation",
    "aix_score",
    "operator.identity"
  ],
  "skills": [
    "github-ops",
    "inventory-check",
    "pdf-to-json",
    "spreadsheet-ops"
  ],
  "protocols": {
    "mcp": "https://ainetcafe.com/mcp/table?s=registry",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": null,
  "aix_score": null,
  "verification": {
    "identity": "none",
    "health": "liveness-only",
    "pricing": "unknown",
    "last_check": "2026-08-15T09:04:11.189Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://ainetcafe.com/duizhang"
    },
    {
      "label": "repository",
      "url": "https://github.com/mario03690/ai-netcafe"
    }
  ],
  "avatar": "https://github.com/mario03690.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/mario03690"
    }
  ],
  "payment_method": "open",
  "unreachable": false,
  "profile": {
    "mcp_server": "netcafe-tables",
    "mcp_version": "1.5.0",
    "tool_count": 10,
    "tools": [
      {
        "name": "csv_to_qbo",
        "description": "Convert a transaction CSV into a .qbo / OFX bank-feed file that QuickBooks and similar accounting software import directly. Needs date, description and amount columns (or debit + credit). Pairs with extract_statement: statement PDF in, importable bank feed out."
      },
      {
        "name": "diff_tables",
        "description": "Matches rows across two CSVs on a key column and reports three things: keys only in A, keys only in B, and keys in both whose other columns disagree — naming the exact column and both values. Unlike reconcile_ledger this needs no amount column, so it also fits name lists, inventory counts, permission tables, and any \"these two exports should match\" check."
      },
      {
        "name": "clean_table",
        "description": "Tidies a spreadsheet export: removes duplicate rows, trims whitespace (half-width and full-width — Chinese exports are full of 　), unifies the half-dozen ways a cell can say \"empty\" (NA / null / - / 无), drops empty rows and columns, and can split one column into several. Returns the cleaned CSV plus exactly what changed: rows in, rows out, duplicates removed, cells trimmed per column. It can also transpose rows/columns and unpivot a wide table into a long one. The row arithmetic is verified in code — if in − removed ≠ out, the response says so instead of handing back a table nobody can check. Use when a CSV came out of Excel or an export and needs cleaning before analysis."
      },
      {
        "name": "merge_tables",
        "description": "Combines up to 20 CSVs into a single table. Headers do not have to match: columns are unioned and a file missing a column contributes blanks for it, so rows never shift silently — the failure mode that makes hand-merged spreadsheets untrustworthy. Reports each source file row count and checks in code that they sum to the merged total. Use for monthly exports, per-store sheets, or any set of files with the same subject but drifting headers."
      },
      {
        "name": "reconcile_ledger",
        "description": "Reconciles two sets of records — your books against a bank, platform, or supplier statement. Matches rows on a key column, compares an amount column, and returns three lists: only in A, only in B, and same key but different amount. Amounts are compared in integer cents, so 0.1 + 0.2 never invents a phantom difference for someone to chase. The response also proves the result: the listed differences are re-added and must equal the gap between the two totals, checked in code. Use for month-end close, platform payouts vs orders, or any \"these two numbers should agree and do not\" problem. This is the job people do by hand with VLOOKUP or a groupby and then cannot prove they got right."
      },
      {
        "name": "fix_csv_encoding",
        "description": "Detect the real encoding of a CSV (GB18030, Shift-JIS, Windows-1252…), repair mojibake (UTF-8 that was read as Latin-1, e.g. \"é\"), and re-emit UTF-8 with a BOM so Excel opens it correctly."
      },
      {
        "name": "csv_to_md_table",
        "description": "CSV (text or URL) → GitHub-flavoured Markdown table."
      },
      {
        "name": "csv_to_chart",
        "description": "CSV (first column = labels, second = values) → chart PNG in one call."
      },
      {
        "name": "csv_to_json",
        "description": "CSV (text or URL) → JSON array of objects (first row = keys). Returns a .json file."
      },
      {
        "name": "json_to_csv",
        "description": "JSON array of objects → CSV file. Flattens keys, quotes fields containing commas."
      }
    ],
    "profiled_at": "2026-08-15T09:04:11.189Z"
  }
}