The Excel to JSON MCP (Model Context Protocol) provides a standardized interface for converting Excel and CSV data into JSON format using the Model Context Protocol. This MCP implementation offers two specific tools for data conversion:
Excel to JSON MCP is part of Excel to JSON by WTSolutions:
Available MCP Servers :
Server Config JSON:
{ "mcpServers": { "excel2json": { "args": [ "mcp-remote", "https://mcp.wtsolutions.cn/sse", "--transport", "sse-only" ], "command": "npx", "tools": [ "excel_to_json_mcp_from_data", "excel_to_json_mcp_from_url" ] } } }
Transport: SSE
URL: https://mcp.wtsolutions.cn/excel-to-json-mcp-sse
Server Config JSON:
{ "mcpServers": { "excel2jsonsse": { "type": "sse", "url": "https://mcp.wtsolutions.cn/sse" } } }
Transport: Streamable HTTP
URL: https://mcp.wtsolutions.cn/excel-to-json-mcp-shttp
Server Config JSON:
{ "mcpServers": { "excel2jsonmcp": { "type": "streamableHttp", "url": "https://mcp.wtsolutions.cn/mcp" } } }excel_to_json_mcp_from_data
Converts tab-separated Excel data or comma-separated CSV text data into JSON format.
Parameter Type Required Description data string Yes Tab-separated or comma-separated text data with at least two rows (header row + data row)Note: Input data must be tab-separated (Excel) or comma-separated (CSV) text with at least two rows (header row + data row).
- The first row will be considered as "header" row, and this MCP will use it as column names, subsequently JSON keys.
- The following rows will be considered as "data" rows, and this MCP will treat them as JSON values.
Convert the following tab-separated data into JSON format:
Name Age IsStudent
John Doe 25 false
Jane Smith 30 true
Convert the following comma-separated data into JSON format:
Name,Age,IsStudent
John Doe,25,false
Jane Smith,30,true
excel_to_json_mcp_from_url
Converts an Excel file from a provided URL into JSON format.
Parameter Type Required Description url string Yes URL pointing to an Excel (.xlsx)Note:
- Each sheet of the Excel file should contain at least two rows (header row + data row).
- The first row will be considered as "header" row, and this MCP will use it as column names, subsequently JSON keys.
- The following rows will be considered as "data" rows, and this MCP will treat them as JSON values.
- This Excel file should be in '.xlsx' format.
- Each sheet of the Excel file will be converted to a JSON object.
- Each JSON object will have 'sheetName' (string) and 'data' (array of objects) properties.
- Each JSON object in 'data' array will have properties corresponding to column names.
- Each JSON object in 'data' array will have values corresponding to cell values.
Convert Excel file to JSON, file URL: https://tools.wtsolutions.cn/example.xlsx
(applicable only when you do not have a URL and working with online AI LLM)
I've jsut uploaded one .xlsx file to you, please extract its URL and send it to MCP tool 'excel_to_json_mcp_from_url', for Excel to JSON conversion.
The MCP tools return a JSON object with the following structure:
Field Type Description isError boolean Indicates if there was an error processing the request msg string 'success' or error description data string Converted data as array of sheet objects if using URL, string if using direct data, '' if there was an error. Each sheet object contains 'sheetName' (string) and 'data' (array of objects) if using URL{ "content": [{ "type": "text", "text": "{\"isError\":false,\"msg\":\"success\",\"data\":\"[{\"Name\":\"John Doe\",\"Age\":25,\"IsStudent\":false},{\"Name\":\"Jane Smith\",\"Age\":30,\"IsStudent\":true}]\"}" }] }
Above is the response from MCP tool, and in most cases your LLM should interpret the response and present you with a JSON object, for example as below.
Note, different LLM models may have different ways to interpret the JSON object, so please check if the JSON object is correctly interpreted by your LLM model.
{ "isError": false, "msg": "success", "data": "[{\"Name\":\"John Doe\",\"Age\":25,\"IsStudent\":false},{\"Name\":\"Jane Smith\",\"Age\":30,\"IsStudent\":true}]" }
{ "isError": false, "msg": "success", "data": [ { "Name": "John Doe", "Age": 25, "IsStudent": false }, { "Name": "Jane Smith", "Age": 30, "IsStudent": true } ] }
[ { "Name": "John Doe", "Age": 25, "IsStudent": false }, { "Name": "Jane Smith", "Age": 30, "IsStudent": true } ]
{ "content": [{ "type": "text", "text": "{\"isError\": true, \"msg\": \"Network Error when fetching file\", \"data\": \"\"}" }] }
Above is the response from MCP tool, and in most cases your LLM should interpret the response and present you with a JSON object, for example as below.
Note, different LLM models may have different ways to interpret the JSON object, so please check if the response is correctly interpreted by your LLM model.
{ "isError": true, "msg": "Network Error when fetching file", "data": "" }
or it is also possbile that your LLM would say "Network Error when fetching file, try again later" to you.
The API automatically detects and converts different data types:
The MCP returns descriptive error messages for common issues:
Excel Data Format Invalid
: When input data is not tab-separated or comma-separatedAt least 2 rows are required
: When input data has fewer than 2 rowsBoth data and url received
: When both 'data' and 'url' parameters are providedNetwork Error when fetching file
: When there's an error downloading the file from the provided URLFile not found
: When the file at the provided URL cannot be foundBlank/Null/Empty cells in the first row not allowed
: When header row contains empty cellsServer Internal Error
: When an unexpected error occursBy using Excel to JSON MCP, you agree to the service agreement, and privacy policy.
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