# Moltbook Monitor & Keyword Alerts (`assmblr/moltbook-intel-scraper`) Actor Monitor Moltbook ("Reddit for AI agents") with incremental sync, keyword alerts, optional comment scraping, and webhook notifications. - **URL**: https://apify.com/assmblr/moltbook-intel-scraper.md - **Developed by:** [Assmblr](https://apify.com/assmblr) (community) - **Categories:** Agents, Automation, Social media - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Moltbook Monitor & Keyword Alerts Monitor Moltbook ("Reddit for AI agents") with **incremental sync**, **keyword alerts**, optional **comment scraping**, and **webhook notifications**. Use this actor when you want Moltbook to behave like a feed you can automate: - schedule it (every 10 minutes / hourly) - only get *new* posts/comments (stateful, deduped) - get notified when something matches your keywords ### What you get - **Incremental runs**: when `incremental=true`, the actor stores state in the Apify KV store and emits only new content. - **Events for automation**: emits dataset items like `new_post`, `new_comment`, `keyword_match`, and (optionally) `comment_thread`. - **Optional comments + thread trees**: fetch comments and optionally reconstruct nested reply trees. - **Webhook delivery**: send events to your system (Slack/Discord/Zapier/custom endpoint). ### Quick start #### 1) Monitor front page (incremental + keyword alerts) ```json { "operation": "monitor", "sort": "new", "limit": 100, "incremental": true, "keywords": ["openclaw", "apify"], "keywordMode": "contains", "includeComments": false, "threadTree": false } ```` #### 2) Monitor specific submolts + comments + webhook ```json { "operation": "monitor", "submolts": ["general", "clawtasks"], "sort": "new", "limit": 50, "includeComments": true, "maxCommentsPerPost": 200, "threadTree": true, "keywords": ["USDC", "Base L2"], "webhookUrl": "https://example.com/webhook" } ``` ### One-off scraping (no monitoring) If you just want a snapshot export, use one of these modes: #### Posts (no comments) ```json { "operation": "posts", "sort": "top", "limit": 200 } ``` #### Posts with comments ```json { "operation": "posts_with_comments", "sort": "new", "limit": 50, "commentSort": "top", "maxCommentsPerPost": 100, "threadTree": true } ``` #### Comments (recent) ```json { "operation": "comments", "limit": 200 } ``` #### Agents (profiles) ```json { "operation": "agents", "limit": 200 } ``` #### Submolts (communities) ```json { "operation": "submolts", "limit": 200 } ``` #### Leaderboard ```json { "operation": "leaderboard", "limit": 200 } ``` #### Search ```json { "operation": "search", "limit": 200, "keywords": ["agents", "payments"] } ``` ### Output Dataset contains: - entities: `post`, `comment`, `agent`, `submolt`, `search_result` - events: emitted as dataset items with `item_type: "event"` KV store values: - `state`: incremental cursor + seen IDs - `events`: raw events array - `verify-report`: run summary ### Pricing (Pay-per-event) This actor uses **pay-per-event** pricing. #### Chargeable events The actor triggers these events in code via `Actor.charge({ eventName })`: - `apify-actor-start` — charged once per run - `include-comments` — charged when comments are fetched (`includeComments=true` or `operation=posts_with_comments`) - `thread-tree` — charged when `threadTree=true` *and* comments are fetched - `webhook-delivery` — charged when `webhookUrl` is set #### Recommended prices (competitive) Suggested values to stay competitive for frequent monitoring: - `apify-actor-start`: **$0.01 / run** - `include-comments`: **$0.02 / run** - `thread-tree`: **$0.01 / run** - `webhook-delivery`: **$0.005 / run** > Note: these prices must be configured in the Actor’s **Monetization** settings on Apify. > If pay-per-event isn’t enabled for the actor/run, `Actor.charge()` is a no-op and the run continues without charging. ### Moltbook API key Moltbook’s official API may require an API key. - If you provide `moltbookApiKey`, the actor uses official API endpoints (more reliable). - Without a key, you may get authorization errors depending on Moltbook’s policy. ### Disclaimer You are responsible for complying with Moltbook’s Terms and for how you use scraped data. # Actor input Schema ## `operation` (type: `string`): monitor = incremental sync + events. Other modes do one-off pulls. ## `sort` (type: `string`): Sort for feeds. ## `submolts` (type: `array`): Submolt slugs to scrape (e.g. general, clawtasks). Empty = front page (posts/posts\_with\_comments/monitor). ## `agentNames` (type: `array`): Optional list of agent usernames to enrich (profiles) and/or filter. ## `postUrls` (type: `array`): Specific post URLs to fetch (post\_urls mode). ## `limit` (type: `integer`): Max posts/items to return for one-off modes. Monitor mode may return less depending on state. ## `includeComments` (type: `boolean`): When enabled, fetch comments for each post (posts\_with\_comments / monitor). ## `commentSort` (type: `string`): Sort to use when fetching comments. ## `maxCommentsPerPost` (type: `integer`): 0 = unlimited (not recommended). ## `threadTree` (type: `boolean`): If enabled, comments are additionally emitted as a nested thread representation (events dataset). ## `incremental` (type: `boolean`): If enabled, only new items since last run are emitted (uses KV store state). ## `since` (type: `string`): Optional override for incremental cutoff. Example: 2026-02-01T00:00:00Z ## `keywords` (type: `array`): Emit keyword\_match events when post/comment content matches any keyword. ## `keywordMode` (type: `string`): contains = substring (case-insensitive), word = whole word match, regex = treat keywords as regex patterns. ## `webhookUrl` (type: `string`): If set, keyword\_match and new\_\* events are POSTed here in batches. ## `webhookHeaders` (type: `object`): Optional headers to include in webhook requests (e.g. Authorization). ## `webhookBatchSize` (type: `integer`): How many events to send per webhook call. ## `moltbookApiKey` (type: `string`): Optional Moltbook API key. If provided, the actor will use the official API endpoints (more reliable than HTML scraping). ## `maxConcurrency` (type: `integer`): Parallel requests (posts/comments/profile enrich). ## `requestTimeoutSecs` (type: `integer`): Per-request timeout for Moltbook API calls (seconds). ## `maxRequestRetries` (type: `integer`): How many times to retry failed requests (network/5xx/timeouts). ## Actor input object example ```json { "operation": "monitor", "sort": "new", "submolts": [], "agentNames": [], "postUrls": [], "limit": 100, "includeComments": false, "commentSort": "top", "maxCommentsPerPost": 200, "threadTree": true, "incremental": true, "since": "", "keywords": [], "keywordMode": "contains", "webhookUrl": "", "webhookHeaders": {}, "webhookBatchSize": 25, "maxConcurrency": 8, "requestTimeoutSecs": 30, "maxRequestRetries": 3 } ``` # Actor output Schema ## `dataset` (type: `string`): No description ## `events` (type: `string`): No description ## `verifyReport` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("assmblr/moltbook-intel-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("assmblr/moltbook-intel-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 assmblr/moltbook-intel-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=assmblr/moltbook-intel-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Moltbook Monitor & Keyword Alerts", "description": "Monitor Moltbook (\"Reddit for AI agents\") with incremental sync, keyword alerts, optional comment scraping, and webhook notifications.", "version": "0.2", "x-build-id": "1tPdqmlODFPvwL1uU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/assmblr~moltbook-intel-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-assmblr-moltbook-intel-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/assmblr~moltbook-intel-scraper/runs": { "post": { "operationId": "runs-sync-assmblr-moltbook-intel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/assmblr~moltbook-intel-scraper/run-sync": { "post": { "operationId": "run-sync-assmblr-moltbook-intel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "operation" ], "properties": { "operation": { "title": "Operation", "enum": [ "monitor", "posts", "posts_with_comments", "post_urls", "comments", "agents", "submolts", "leaderboard", "search" ], "type": "string", "description": "monitor = incremental sync + events. Other modes do one-off pulls.", "default": "monitor" }, "sort": { "title": "Sort", "enum": [ "hot", "new", "top", "rising" ], "type": "string", "description": "Sort for feeds.", "default": "new" }, "submolts": { "title": "Submolts", "type": "array", "description": "Submolt slugs to scrape (e.g. general, clawtasks). Empty = front page (posts/posts_with_comments/monitor).", "default": [], "items": { "type": "string" } }, "agentNames": { "title": "Agent names", "type": "array", "description": "Optional list of agent usernames to enrich (profiles) and/or filter.", "default": [], "items": { "type": "string" } }, "postUrls": { "title": "Post URLs", "type": "array", "description": "Specific post URLs to fetch (post_urls mode).", "default": [], "items": { "type": "string" } }, "limit": { "title": "Limit", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Max posts/items to return for one-off modes. Monitor mode may return less depending on state.", "default": 100 }, "includeComments": { "title": "Include comments", "type": "boolean", "description": "When enabled, fetch comments for each post (posts_with_comments / monitor).", "default": false }, "commentSort": { "title": "Comment sort", "enum": [ "top", "new", "controversial" ], "type": "string", "description": "Sort to use when fetching comments.", "default": "top" }, "maxCommentsPerPost": { "title": "Max comments per post", "minimum": 0, "maximum": 5000, "type": "integer", "description": "0 = unlimited (not recommended).", "default": 200 }, "threadTree": { "title": "Build thread tree", "type": "boolean", "description": "If enabled, comments are additionally emitted as a nested thread representation (events dataset).", "default": true }, "incremental": { "title": "Incremental (stateful)", "type": "boolean", "description": "If enabled, only new items since last run are emitted (uses KV store state).", "default": true }, "since": { "title": "Since (ISO timestamp)", "type": "string", "description": "Optional override for incremental cutoff. Example: 2026-02-01T00:00:00Z", "default": "" }, "keywords": { "title": "Keywords", "type": "array", "description": "Emit keyword_match events when post/comment content matches any keyword.", "default": [], "items": { "type": "string" } }, "keywordMode": { "title": "Keyword mode", "enum": [ "contains", "word", "regex" ], "type": "string", "description": "contains = substring (case-insensitive), word = whole word match, regex = treat keywords as regex patterns.", "default": "contains" }, "webhookUrl": { "title": "Webhook URL (optional)", "type": "string", "description": "If set, keyword_match and new_* events are POSTed here in batches.", "default": "" }, "webhookHeaders": { "title": "Webhook headers", "type": "object", "description": "Optional headers to include in webhook requests (e.g. Authorization).", "default": {} }, "webhookBatchSize": { "title": "Webhook batch size", "minimum": 1, "maximum": 200, "type": "integer", "description": "How many events to send per webhook call.", "default": 25 }, "moltbookApiKey": { "title": "Moltbook API key (optional)", "type": "string", "description": "Optional Moltbook API key. If provided, the actor will use the official API endpoints (more reliable than HTML scraping)." }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 50, "type": "integer", "description": "Parallel requests (posts/comments/profile enrich).", "default": 8 }, "requestTimeoutSecs": { "title": "Request timeout (secs)", "minimum": 5, "maximum": 180, "type": "integer", "description": "Per-request timeout for Moltbook API calls (seconds).", "default": 30 }, "maxRequestRetries": { "title": "Max request retries", "minimum": 0, "maximum": 10, "type": "integer", "description": "How many times to retry failed requests (network/5xx/timeouts).", "default": 3 } } }, "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 } } } } } } } } } } ```