# TMDB Movie & TV Metadata Scraper (`jungle_synthesizer/tmdb-movie-tv-metadata-scraper`) Actor Scrape rich metadata for movies and TV shows from The Movie Database (TMDB) — no API key required. Discovers titles from public browse pages and extracts full detail records including cast, directors, genres, keywords, ratings, runtime, and production companies. - **URL**: https://apify.com/jungle\_synthesizer/tmdb-movie-tv-metadata-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Videos, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 ## TMDB Movie & TV Metadata Scraper Scrape rich metadata for movies and TV shows from [The Movie Database (TMDB)](https://www.themoviedb.org/) — **no API key required**. Discovers titles from TMDB's public discover/browse pages and extracts full detail records including cast, directors, genres, keywords, ratings, runtime, original language, and production companies. ### What you get Each record in the output dataset contains: | Field | Description | |-------|-------------| | `tmdb_id` | Numeric TMDB ID | | `title` | Movie or TV show title | | `media_type` | `movie` or `tv` | | `tmdb_url` | Canonical TMDB page URL | | `original_title` | Title in the original language | | `release_date` | First release or air date (YYYY-MM-DD) | | `vote_average` | Aggregate rating (0–10 scale) | | `vote_count` | Number of votes | | `user_score_percent` | User score percentage (0–100) | | `overview` | Plot summary or show description | | `genres` | Comma-separated genre names | | `runtime_minutes` | Runtime in minutes | | `original_language` | Original language | | `production_companies` | Comma-separated production company names | | `imdb_id` | IMDb ID (e.g. `tt0137523`) — when listed on the TMDB page | | `cast_top` | Comma-separated top-billed cast names | | `directors` | Comma-separated director names | | `keywords` | Comma-separated TMDB keyword tags | ### Why use this instead of the TMDB API? Most TMDB scrapers on the Apify Store are thin wrappers around the TMDB REST API — they require you to register for and manage your own API key and stay within TMDB's per-account rate limits. This actor scrapes TMDB's **public web pages** directly, so: - No API key registration or management - No per-account rate limits to worry about - Both movies and TV shows in one unified output schema - Includes fields not always easily queryable via API (IMDb cross-ID, keyword tags, top cast) ### Inputs | Input | Type | Default | Description | |-------|------|---------|-------------| | `maxItems` | integer | 15 | Maximum number of records to return. Set to `0` for no limit. | | `mediaType` | string | `both` | Which media type to scrape: `movie`, `tv`, or `both`. | | `startPage` | integer | 1 | Discover page to start from (each page has ~20 titles). | ### Example use cases - **Media server catalogs**: Build or enrich metadata catalogs for Plex, Jellyfin, or Kodi libraries without managing API credentials. - **Recommendation engines**: Feed movie/TV metadata into ML pipelines — genres, keywords, cast, and ratings in one schema. - **Cross-referencing**: Use `imdb_id` to join TMDB data with IMDb datasets for enriched analytics. - **Market research**: Track ratings and popularity trends across the TMDB catalog over time. ### How it works 1. **Discover**: Crawls paginated TMDB browse pages (`/movie?language=en-US&page=N`, `/tv?...`) — 20 titles per page, up to 500 pages per type. 2. **Detail**: For each title, fetches the detail page and extracts: - **JSON-LD** (`schema.org Movie` / `TVSeries`): name, description, rating, genres, runtime, release date - **DOM**: user score chart, directors, cast, keywords, original title, language, production companies ### Notes - TMDB's discover pages order titles by popularity (most popular first). Use `startPage` to offset into the catalog. - The `imdb_id` field is populated only when TMDB links to IMDb on the detail page — this is common for well-known titles but may be absent for obscure entries. - Runtime is in minutes for movies. For TV shows, TMDB typically reports the average episode length. - The `language=en-US` parameter is appended to all requests to ensure English metadata in the output. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of records to scrape. Set to 0 for no limit. ## `mediaType` (type: `string`): Which media type to scrape: 'movie', 'tv', or 'both'. ## `startPage` (type: `integer`): Discover page number to start from (1-indexed). ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "mediaType": "both", "startPage": 1 } ```` # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "mediaType": "both", "startPage": 1 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/tmdb-movie-tv-metadata-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "mediaType": "both", "startPage": 1, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/tmdb-movie-tv-metadata-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "mediaType": "both", "startPage": 1 }' | apify call jungle_synthesizer/tmdb-movie-tv-metadata-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/tmdb-movie-tv-metadata-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TMDB Movie & TV Metadata Scraper", "description": "Scrape rich metadata for movies and TV shows from The Movie Database (TMDB) — no API key required. Discovers titles from public browse pages and extracts full detail records including cast, directors, genres, keywords, ratings, runtime, and production companies.", "version": "0.1", "x-build-id": "1gRPzNk114EKSVjGk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~tmdb-movie-tv-metadata-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-tmdb-movie-tv-metadata-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/jungle_synthesizer~tmdb-movie-tv-metadata-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-tmdb-movie-tv-metadata-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/jungle_synthesizer~tmdb-movie-tv-metadata-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-tmdb-movie-tv-metadata-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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to scrape. Set to 0 for no limit.", "default": 15 }, "mediaType": { "title": "Media Type", "enum": [ "movie", "tv", "both" ], "type": "string", "description": "Which media type to scrape: 'movie', 'tv', or 'both'.", "default": "both" }, "startPage": { "title": "Start Page", "type": "integer", "description": "Discover page number to start from (1-indexed).", "default": 1 } } }, "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 } } } } } } } } } } ```