# JMA Japan Forecast Scraper (`parseforge/jma-japan-forecast-scraper`) Actor Tap the Japan Meteorological Agency feed for prefecture level forecasts. Returns area name, forecast date, weather, wind, and wave conditions for Tokyo, Osaka, Hokkaido, Okinawa, and every other JMA office region. Useful for weather dashboards and travel apps across Japan. - **URL**: https://apify.com/parseforge/jma-japan-forecast-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Travel, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.90 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐ŸŒค JMA Japan Forecast Scraper > ๐Ÿš€ **Scrape Japan Meteorological Agency regional weather forecasts.** > ๐Ÿ•’ **Last updated** 2026-07-17 ยท **๐Ÿ“Š 9 fields** per record ยท **no API key needed** Export to spreadsheet, JSON, JSONL, XML, RSS, or HTML. Every record is mapped to a consistent schema - area, code, weather code, weather description, wind, wave and more, so you can filter, join and export without any glue code. No account or API key required to try it. | ๐ŸŽฏ Target Audience | ๐Ÿ’ก Primary Use Cases | |---|---| | Analysts, developers, researchers and operators who need this data as clean rows | Data collection, enrichment, monitoring, and feeding apps, sheets or models | ### ๐Ÿ“‹ What the JMA Japan Forecast Scraper does - Collects the records you ask for as clean, structured rows - Returns 9 fields per record including area, code, weather code, weather description, wind, wave - Consistent, flat schema - ready for a spreadsheet, database or app - Exports to CSV, Excel, JSON, or XML > ๐Ÿ’ก **Why it matters:** the raw source returns nested, paged responses. This Actor flattens them into one clean row per record, so the data drops straight into your workflow. ### ๐ŸŽฌ Full Demo (_๐Ÿšง Coming soon_) ### โš™๏ธ Input | Field | Type | Description | |---|---|---| | `maxItems` | integer | Cap on the number of results. Free: 10. Paid: up to 1,000,000. | | `prefectureCode` | string | JMA prefecture office code. e.g. `130000`. | ```` {"maxItems":25,"prefectureCode":"130000"} ```` ### ๐Ÿ“Š Output Each item is one record with 9 fields: | Field | Type | Description | |---|---|---| | `area` | string | Area | | `code` | string | Code | | `weatherCode` | string | Weather Code | | `weatherDescription` | string | Description | | `wind` | string | Wind | | `wave` | string | Wave | | `temps` | string | Temps | | `reportDatetime` | string | Report Datetime | | `scrapedAt` | string | Scraped At | ### โœจ Why choose this Actor - Clean, flat schema - ready to use - No API key or account needed - Export to CSV, Excel, JSON, or XML - Pay-per-event billing - only pay for records returned ### ๐Ÿš€ How to use 1. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. Open the Actor on Apify Console 3. Fill in the input fields 4. Click Start 5. Download the results as CSV, Excel, JSON, or XML ### ๐Ÿ’ผ Use cases **Research and analysis** - study the data at scale in your own tools. **Enrichment** - add structured records to a database, sheet or app. **Monitoring** - track changes over time with scheduled runs. **Datasets** - build clean datasets for reporting, dashboards or models. ### ๐Ÿ”Œ Automating JMA Japan Forecast Scraper Trigger the Actor via Make, Zapier, Slack, Airbyte, GitHub Actions, Google Drive, n8n or any HTTP webhook on Apify's integration platform. ### ๐Ÿค– Ask an AI assistant about this scraper Paste this README into ChatGPT, Claude, Perplexity or Copilot and ask how to integrate the data into your workflow. ### โ“ Frequently Asked Questions **โ“ Do I need an API key?** No - just set the input and run. **โ“ Free users?** Capped at 10 items per run - perfect for testing. **โ“ What output formats?** CSV, Excel, JSON, or XML - pick on the Storage tab. **โ“ Is the data live?** Yes - fetched at run time from www.jma.go.jp. **โ“ Can I schedule it?** Yes - use Apify's scheduler or any webhook integration. ### ๐Ÿ”Œ Integrate with any app Apify provides webhooks, REST API, scheduled runs, dataset downloads, and integrations with Make, Zapier, n8n, Slack, Google Drive, Airbyte, GitHub Actions, and more. > ๐Ÿ’ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more scrapers and all-in-one combos. **๐Ÿ†˜ Need Help?** [Open our contact form](https://tally.so/r/BzdKgA) > **โš ๏ธ Disclaimer:** independent tool, not affiliated with any data source named above. Only publicly available data is collected. # Actor input Schema ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## `prefectureCode` (type: `string`): JMA prefecture office code. ## Actor input object example ```json { "maxItems": 10, "prefectureCode": "130000" } ```` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "maxItems": 10, "prefectureCode": "130000" }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/jma-japan-forecast-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "maxItems": 10, "prefectureCode": "130000", } # Run the Actor and wait for it to finish run = client.actor("parseforge/jma-japan-forecast-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10, "prefectureCode": "130000" }' | apify call parseforge/jma-japan-forecast-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/jma-japan-forecast-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "JMA Japan Forecast Scraper", "description": "Tap the Japan Meteorological Agency feed for prefecture level forecasts. Returns area name, forecast date, weather, wind, and wave conditions for Tokyo, Osaka, Hokkaido, Okinawa, and every other JMA office region. Useful for weather dashboards and travel apps across Japan.", "version": "0.1", "x-build-id": "XCl9CH4RLDYXTXZg0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~jma-japan-forecast-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-jma-japan-forecast-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~jma-japan-forecast-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-jma-japan-forecast-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~jma-japan-forecast-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-jma-japan-forecast-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "maxItems": { "title": "Maximum forecasts", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" }, "prefectureCode": { "title": "Prefecture code", "enum": [ "130000", "270000", "016000", "015000", "014100", "012000", "011000", "040000", "050000", "060000", "070000", "080000", "090000", "100000", "110000", "120000", "140000", "150000", "160000", "170000", "180000", "190000", "200000", "210000", "220000", "230000", "240000", "250000", "260000", "280000", "290000", "300000", "310000", "320000", "330000", "340000", "350000", "360000", "370000", "380000", "390000", "400000", "410000", "420000", "430000", "440000", "450000", "460100", "471000", "472000", "473000", "474000" ], "type": "string", "description": "JMA prefecture office code." } } }, "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 } } } } } } } } } } ```