# ChatWork Room Data Extractor (`cloud9_ai/chatwork-scraper`) Actor Extract ChatWork room data via API: messages, members, tasks, file metadata. Export chat history, analyze team communication, automate workflow reports. Japan's leading business chat platform for enterprise collaboration. - **URL**: https://apify.com/cloud9\_ai/chatwork-scraper.md - **Developed by:** [cloud9](https://apify.com/cloud9_ai) (community) - **Categories:** Integrations, Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.50 / 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. 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 ## ChatWork Scraper Extract conversations, member lists, and tasks from ChatWork rooms via the ChatWork API v2. Export team collaboration data for analysis, archiving, and integration. ### Features - **Extract Room Data**: Retrieve all room information including message counts, file counts, and task counts - **Message Export**: Fetch and export messages with sender details, timestamps, and message bodies - **Member Management**: Extract room member lists with roles, departments, and organization info - **Task Tracking**: Download tasks with assignments, deadlines, and status information - **Flexible Filtering**: Target specific rooms or process all rooms in your workspace - **Configurable Limits**: Control message retrieval limits (1-1000 per room) - **Rate Limiting**: Built-in delays to respect ChatWork API rate limits - **Structured Output**: JSON format ready for integration with downstream tools ### Use Cases - **Team Communication Audit**: Extract and analyze conversation history for compliance and documentation - **Knowledge Base Building**: Export team discussions and decisions for internal wikis and knowledge repositories - **Project Handover**: Collect room data, members, and task status for project transitions - **Data Backup**: Create comprehensive backups of ChatWork conversations and collaboration data - **Analytics Integration**: Export team communication metrics to BI tools and analytics platforms - **Migration Support**: Prepare ChatWork data for integration with other communication platforms ### Input ```json { "apiToken": "your-chatwork-api-token", "roomIds": ["123456", "789012"], "includeMessages": true, "includeMembers": true, "includeTasks": true, "messageLimit": 100 } ```` #### Input Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `apiToken` | string | Yes | - | ChatWork API token for authentication. Get this from ChatWork Account Settings > API Token | | `roomIds` | array | No | - | Specific room IDs to scrape. If empty, all accessible rooms will be fetched | | `includeMessages` | boolean | No | true | Whether to fetch messages for each room | | `includeMembers` | boolean | No | false | Whether to fetch member list for each room | | `includeTasks` | boolean | No | false | Whether to fetch tasks for each room | | `messageLimit` | integer | No | 100 | Maximum number of messages to fetch per room (1-1000) | ### Output ```json { "roomId": 123456, "roomName": "Development Team", "roomType": "group", "role": "admin", "messageCount": 1520, "fileCount": 45, "taskCount": 12, "lastUpdateTime": "2024-02-12T15:30:45.000Z", "messages": [ { "messageId": "msg123456", "senderName": "John Doe", "senderId": 98765, "body": "Great work on the project!", "sendTime": "2024-02-12T14:20:00.000Z", "updateTime": "2024-02-12T14:21:00.000Z" } ], "members": [ { "accountId": 98765, "name": "John Doe", "chatworkId": "john.doe", "role": "admin", "organizationName": "Engineering", "department": "Backend Team" } ], "tasks": [ { "taskId": 54321, "body": "Review pull request", "assignedTo": "Jane Smith", "assignedBy": "John Doe", "status": "open", "limitTime": "2024-02-15T17:00:00.000Z", "limitType": "time" } ] } ``` ### Pricing **$2.50 per 1,000 API calls** #### Example Costs | Scenario | API Calls | Cost | |----------|-----------|------| | 10 rooms, messages only | 11 | $0.03 | | 50 rooms with members | 101 | $0.25 | | 100 rooms with messages + members + tasks | 301 | $0.75 | | 500 rooms, all data types | 1,501 | $3.75 | **Note**: Each room data fetch = 1 call, each message fetch = 1 call, each member fetch = 1 call, each task fetch = 1 call. ### Tips 1. **Get Your API Token**: Log in to ChatWork, go to Account Settings > API Token tab, and copy your personal API token 2. **Start with Small Tests**: Use `roomIds` parameter to test with 1-2 rooms before processing all rooms 3. **Control Message Volume**: Adjust `messageLimit` based on your needs. Lower values (50-100) are faster; higher values (500+) extract more history 4. **Optimize with Flags**: Disable `includeMembers` and `includeTasks` if you only need messages to reduce API calls 5. **Handle Rate Limits**: The scraper includes 500ms delays between API requests to respect ChatWork's rate limits 6. **Room IDs as Strings**: Convert numeric room IDs to strings when specifying in `roomIds` array 7. **Export Frequency**: Consider scheduling this actor to run daily or weekly for backup and monitoring use cases ### Integrations Export your extracted ChatWork data to: - **Google Sheets**: Use Apify's Google Sheets integration to automatically append rows - **Excel/CSV**: Download dataset as CSV and open in Excel or Google Sheets - **Webhooks**: Send data to your custom webhooks for real-time processing - **REST API**: Query extracted data via Apify's API - **Zapier/Make**: Connect via webhooks to automate downstream workflows - **Data Warehouse**: Export to BigQuery, Snowflake, or PostgreSQL - **Slack**: Post summaries to Slack channels using webhooks ### Support For issues, feature requests, or questions: - Check the [Apify community forum](https://apify.com/community) - Review [ChatWork API documentation](https://developer.chatwork.com/docs/overview) - Open an issue on the [project repository](https://github.com/your-org/chatwork-scraper) ### License Apache-2.0 License # Actor input Schema ## `apiToken` (type: `string`): ChatWork API token for authentication ## `roomIds` (type: `array`): Specific room IDs to scrape. If empty, all rooms will be fetched. ## `includeMessages` (type: `boolean`): Whether to fetch messages for each room ## `includeMembers` (type: `boolean`): Whether to fetch member list for each room ## `includeTasks` (type: `boolean`): Whether to fetch tasks for each room ## `messageLimit` (type: `integer`): Maximum number of messages to fetch per room (default: 100) ## Actor input object example ```json { "includeMessages": true, "includeMembers": false, "includeTasks": false, "messageLimit": 100 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("cloud9_ai/chatwork-scraper").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 = {} # Run the Actor and wait for it to finish run = client.actor("cloud9_ai/chatwork-scraper").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 '{}' | apify call cloud9_ai/chatwork-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=cloud9_ai/chatwork-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ChatWork Room Data Extractor", "description": "Extract ChatWork room data via API: messages, members, tasks, file metadata. Export chat history, analyze team communication, automate workflow reports. Japan's leading business chat platform for enterprise collaboration.", "version": "0.1", "x-build-id": "fqCiwUXyY7wVCCgH0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/cloud9_ai~chatwork-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-cloud9_ai-chatwork-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/cloud9_ai~chatwork-scraper/runs": { "post": { "operationId": "runs-sync-cloud9_ai-chatwork-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/cloud9_ai~chatwork-scraper/run-sync": { "post": { "operationId": "run-sync-cloud9_ai-chatwork-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "apiToken" ], "properties": { "apiToken": { "title": "API Token", "type": "string", "description": "ChatWork API token for authentication" }, "roomIds": { "title": "Room IDs", "type": "array", "description": "Specific room IDs to scrape. If empty, all rooms will be fetched.", "items": { "type": "string" } }, "includeMessages": { "title": "Include Messages", "type": "boolean", "description": "Whether to fetch messages for each room", "default": true }, "includeMembers": { "title": "Include Members", "type": "boolean", "description": "Whether to fetch member list for each room", "default": false }, "includeTasks": { "title": "Include Tasks", "type": "boolean", "description": "Whether to fetch tasks for each room", "default": false }, "messageLimit": { "title": "Message Limit", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of messages to fetch per room (default: 100)", "default": 100 } } }, "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 } } } } } } } } } } ```