# Excel to JSON Converter — XLSX/XLS by URL, All Sheets, API (`eliai/excel-to-json`) Actor Convert Excel to JSON via API. Input: a URL to an .xlsx or .xls file. Output: JSON with every sheet as an array of row objects, headers detected automatically. Handles multi-sheet workbooks. Flat, cheap pay-per-file pricing — one charge per converted file. - **URL**: https://apify.com/eliai/excel-to-json.md - **Developed by:** [Anthony Snider](https://apify.com/eliai) (community) - **Categories:** Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $30.00 / 1,000 file converteds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Excel (XLSX) to JSON Converter Turn any Excel workbook URL into clean, structured JSON — every sheet as an array of row objects, headers detected automatically. **Live on the Apify Store — run it instantly or call it as an agent tool via Apify MCP.** ### What you get - Point it at any `.xlsx` / `.xls` file URL and get back parsed JSON. - Every sheet converted to an array of row objects keyed by the detected header row. - `sheetNames`, per-sheet `columns`, `rowCount`, and `rows`. - Pick a single sheet by name or index, cap rows, or convert in bulk. ### Input ```json { "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx", "sheet": "Sheet1", "maxRows": 1000 } ```` - `url` — direct URL to the Excel workbook (required). - `urls` — optional array of extra workbook URLs (up to 25 total per run). - `sheet` — optional sheet name or 0-based index; omit to convert every sheet. - `maxRows` — optional cap on data rows per sheet (default 5000). ### Output ```json { "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx", "finalUrl": "https://raw.githubusercontent.com/SheetJS/test_files/master/AutoFilter.xlsx", "status": 200, "sheetNames": ["Sheet1"], "sheets": { "Sheet1": { "rowCount": 3, "columns": ["Column1", "Column2"], "rows": [ { "Column1": "a", "Column2": 1 }, { "Column1": "b", "Column2": 2 } ] } } } ``` Each input produces one dataset item. Failed inputs return `{ url, error }` so one bad file never breaks the run. # Actor input Schema ## `url` (type: `string`): Direct URL to an .xlsx or .xls workbook to convert. ## `urls` (type: `array`): Optional list of additional Excel file URLs to convert in one run (max 25 total). ## `sheet` (type: `string`): Convert only this sheet. Accepts a sheet name or a 0-based index. Leave empty to convert all sheets. ## `maxRows` (type: `integer`): Cap the number of data rows returned per sheet (header row excluded). ## Actor input object example ```json { "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx", "maxRows": 5000 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx" }; // Run the Actor and wait for it to finish const run = await client.actor("eliai/excel-to-json").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx" } # Run the Actor and wait for it to finish run = client.actor("eliai/excel-to-json").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx" }' | apify call eliai/excel-to-json --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=eliai/excel-to-json", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Excel to JSON Converter — XLSX/XLS by URL, All Sheets, API", "description": "Convert Excel to JSON via API. Input: a URL to an .xlsx or .xls file. Output: JSON with every sheet as an array of row objects, headers detected automatically. Handles multi-sheet workbooks. Flat, cheap pay-per-file pricing — one charge per converted file.", "version": "0.1", "x-build-id": "esDuXQMqg1RcV4PSE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/eliai~excel-to-json/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-eliai-excel-to-json", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/eliai~excel-to-json/runs": { "post": { "operationId": "runs-sync-eliai-excel-to-json", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/eliai~excel-to-json/run-sync": { "post": { "operationId": "run-sync-eliai-excel-to-json", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "url" ], "properties": { "url": { "title": "Excel file URL", "type": "string", "description": "Direct URL to an .xlsx or .xls workbook to convert." }, "urls": { "title": "Excel file URLs (bulk)", "type": "array", "description": "Optional list of additional Excel file URLs to convert in one run (max 25 total).", "items": { "type": "string" } }, "sheet": { "title": "Sheet (optional)", "type": "string", "description": "Convert only this sheet. Accepts a sheet name or a 0-based index. Leave empty to convert all sheets." }, "maxRows": { "title": "Max rows per sheet", "minimum": 1, "type": "integer", "description": "Cap the number of data rows returned per sheet (header row excluded).", "default": 5000 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```