Ledgermoor Table to Excel

Turn any table into a real .xlsx or CSV file: numbers stay numbers, header frozen. Free, no storage.

Should I use this

Quality & Safety

A
Description quality
100%
Schema completeness
95%
Naming quality
80%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~313Tokens (tool definitions)
~1.8 KBTypical response size
Minimal attention impact (0.24% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "ledgermoor": {
      "url": "https://gpt-ledgermoor.cybermaxtools.com/mcp?via=mcp-registry"
    }
  }
}

Remote endpoints

https://gpt-ledgermoor.cybermaxtools.com/mcp?via=mcp-registrystreamable-http
https://chatgpt-apps.cybermax-tools.workers.dev/ledgermoor/mcp?via=mcp-registrystreamable-http

What it can do

Tool inventory

Tools (1)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢table_to_excel(title, headers, rows, sheetName)

Use this when the user wants a table turned into an Excel spreadsheet (.xlsx) or a CSV file: "convert this PDF table to Excel", "make this into a spreadsheet", "export to CSV", "PDF to Excel", "screenshot to Excel". First read the table yourself from the uploaded file, image or text, then pass the header row and every data row exactly as written (keep currency signs and minus signs; do not total or reorder). Returns download links for .xlsx and .csv and a preview.

Input Schema

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string",
      "description": "What the table is, e.g. \"March bank transactions\" (used for the file name)"
    },
    "headers": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Column names (the header row)"
    },
    "rows": {
      "type": "array",
      "minItems": 1,
      "maxItems": 1000,
      "items": {
        "type": "array",
        "items": {
          "type": [
            "string",
            "number",
            "null"
          ]
        }
      },
      "description": "Data rows, each an array of cell values in column order",
      "examples": [
        [
          [
            "2026-10-01",
            "Coffee beans",
            "-12.50"
          ],
          [
            "2026-10-02",
            "Client payment",
            "1,250.00"
          ]
        ]
      ]
    },
    "sheetName": {
      "type": "string"
    }
  },
  "required": [
    "rows"
  ],
  "additionalProperties": false
}

Community

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Evidence

Recent observations

verifiedversion not recorded1 tools
verifiedversion not recorded1 tools