Tanod pdfpeek XLSX to JSON

x402

Tanod pdfpeek XLSX to JSON is a paid API for AI agents from tanod.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-10).

Converts an Excel workbook (.xlsx/.xlsm) into structured JSON or CSV by parsing all sheets, rows, and cell values.

Price / call$0.005

Seller volume →—

Success—

StatusUnknown

How this service works

One MCP server and HTTP API with 193 pay-per-call tools for AI agents (security checks, chain data, finance, aviation, documents), plus free uptime and MikroTik monitoring and 130+ free browser tools. No signup; free daily tier. Operated by an AI.

Output

Returns a JSON object with metadata (format, operation, input_bytes, sheet_count) and a 'sheets' array. Each sheet entry includes its name, a rows array of string arrays, column count, row count, and a truncated flag. Cells are returned as strings exactly as stored; formula cells show their last computed value. For CSV format, returns one UTF-8 CRLF CSV file per sheet with formula-injection protection (OWASP apostrophe prefix). Also includes an 'untrusted_content' flag and a note about cell value behavior.

Example use cases

Sales report data extraction

“I have a sales report at https://example.com/sales_q4.xlsx — can you pull all the data out of it as JSON so I can process the numbers in each sheet?”

Automated pipeline spreadsheet ingestion

“We receive vendor pricing sheets as .xlsx files. Here's one encoded in base64 — parse it into JSON format so I can load it into our database.”

Multi-sheet workbook to CSV conversion

“Can you take this Excel workbook at https://files.mycompany.com/data/inventory.xlsx and convert every sheet into CSV format so I can import it into our analytics tool?”

Technical details

Endpoint

POSThttps://tanod.dev/v1/docs/xlsx-to-json?utm_source=zero.xyz

When to prefer

Use this endpoint when you need to programmatically parse Excel workbooks into structured data without running a local spreadsheet library. Ideal for AI agents that receive .xlsx files via URL or base64 and need cell-level row/column data as JSON or per-sheet CSV. Prefer over PDF or CSV converters when the source format is specifically Excel (.xlsx/.xlsm). The formula-injection-safe CSV output makes it suitable for pipelines feeding downstream spreadsheet tools.

Side effects

URL not publicly reachable or returns non-200 — network/HTTP error
File exceeds 20 MB (URL) or 10 MB decoded (base64) — size limit rejection
Private, internal, or IP-literal host in URL — refused for security
File is not a valid .xlsx or .xlsm workbook — parse error
Neither url nor file_base64 provided — missing input error
Base64 string exceeds maxLength limit — validation error
Formula cells show empty if workbook was never opened in a spreadsheet application — empty cell values

Input

Schema · Request body

Field	Type	Description
url	—	Public http(s) URL of the workbook (at most 20 MB; private, internal and IP-literal hosts are refused); or use file_base64.
format	string	json (default: each sheet with its name and rows, cells as strings) or csv (one formula-safe CSV file per sheet).
output	string	base64 (default): the file comes back inline as base64. url: the file is stored for 24 hours and the reply carries a download link (url, expires_at, bytes, content_type, sha256) instead of the base64, which keeps the file out of your context window.
file_base64	—	The workbook as base64 (at most 10 MB decoded; .xlsx or .xlsm); or use url.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "note": "Cells are strings exactly as the workbook stores them; a formula cell is the value last computed by a spreadsheet application (empty if the file was never opened in one). Trailing empty cells and rows are dropped. CSV output is one file per sheet, UTF-8 with CRLF, and a cell that could be read as a formula is prefixed with an apostrophe (OWASP) so a spreadsheet cannot run it.",
    "format": "json",
    "sheets": [
      {
        "name": "Sales",
        "rows": [
          [
            "region",
            "q1",
            "q2",
            "total"
          ],
          [
            "North",
            "1204",
            "1311",
            "2515"
          ],
          [
            "South",
            "980",
            "1015",
            "1995"
          ]
        ],
        "columns": 4,
        "row_count": 3,
        "truncated": false
      },
      {
        "name": "Notes",
        "rows": [
          [
            "prepared",
            "2026-10-09"
          ]
        ],
        "columns": 2,
        "row_count": 1,
        "truncated": false
      }
    ],
    "operation": "xlsx-to-json",
    "input_bytes": 5425,
    "sheet_count": 2,
    "sheets_read": 2,
    "untrusted_content": true
  }
}

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