# IMDb Search Scraper (`dami_studio/imdb-scraper`) Actor Search IMDb for movies, TV shows and people using IMDb's own public suggestion API — no key, no login. Get clean rows with id, title/name, type, year, stars/known-for, poster image and the imdb.com URL. Pass multiple queries to fetch more. - **URL**: https://apify.com/dami\_studio/imdb-scraper.md - **Developed by:** [Dami's Studio](https://apify.com/dami_studio) (community) - **Categories:** Integrations, AI, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $3.00 / 1,000 item returneds 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 ## IMDb Search Scraper Search IMDb for movies, TV shows and people using IMDb's **own public suggestion API** — the same endpoint that powers the autocomplete in IMDb's search box. No API key, no login, no scraping HTML. Give it a query like `breaking bad` or `tom hanks` and get back clean, structured rows: the IMDb id, title/name, type, year, the "stars / known for" line, the poster/headshot image, and the canonical `imdb.com` URL. ### What you get per result | Field | Notes | |---|---| | `id` | IMDb id, e.g. `tt0903747` (title), `nm0000158` (person), `co...` (company). | | `kind` | `title`, `person`, `company`, or `other` — derived from the id prefix. | | `title` | The title or person name. | | `category` | IMDb's type label, e.g. `feature`, `TV series`, `video game`, `video`. Null for people. | | `year` | Release year (titles). Null when not applicable. | | `yearRange` | Run span for series, e.g. `2008-2013`. Null when not applicable. | | `starsOrKnownFor` | Main cast for a title, or the "known for" line for a person (e.g. `Producer, Cast Away (2000)`). | | `rank` | IMDb popularity rank (lower = more popular). | | `image` | Poster / headshot URL. Null when IMDb has no image. | | `url` | Canonical IMDb URL: `imdb.com/title/{id}/` or `imdb.com/name/{id}/`. | ### Input | Field | Notes | |---|---| | `query` | A single search term — a movie, show, or person name. | | `queries` | An array of terms searched in one run; results are merged and de-duplicated by id. Use this to get more than ~8 results. | | `type` | `all` (default), `titles` (ids starting `tt`), or `people` (ids starting `nm`). | | `maxItems` | Cap on the number of de-duplicated rows returned (default 50). | #### Important: no pagination The IMDb suggestion API returns a **fixed ~8 results per query** and has **no pagination**. If you set `maxItems` higher than that, the actor simply returns what's available (and logs it). To get more results, pass several related terms in `queries` — each is fetched separately and the rows are de-duplicated by IMDb id. ### Output One dataset row per de-duplicated result, flagged `ok: true`. Pricing is pay-per-result — you are only charged for genuine result rows. Nothing is charged for: - empty/invalid input (a single `ok: false` row with `errorCode: "BAD_INPUT"`), - no results for the query (`NO_RESULTS`), - rate limits or network errors (`RATE_LIMITED` / `NETWORK`). #### Proxy The suggestion API is a public, no-auth endpoint with no anti-bot, so **no proxy is required** and the default runs without one (saving proxy credits). Only enable Apify Proxy if you hit IP rate limits at very high volume. #### Troubleshooting - Got a `NO_RESULTS` row with `type` set? The suggestion API may have returned only other kinds (e.g. all titles when you asked for people). Try `type: "all"`. - Want more than ~8 rows? That's the API's per-query cap — add more terms to `queries`. ### Examples ```json { "query": "breaking bad", "maxItems": 10 } ```` ```json { "query": "tom hanks", "type": "people" } ``` ```json { "queries": ["inception", "the matrix"], "type": "titles" } ``` # Actor input Schema ## `query` (type: `string`): A single thing to search IMDb for — a movie, TV show or person name, e.g. "breaking bad" or "tom hanks". For several searches at once, use the "queries" field below instead (or as well). ## `queries` (type: `array`): Run several searches in one go — one request per term, results merged and de-duplicated by IMDb id. Use this to get more than the ~8 results a single query returns (the suggestion API has no pagination). Example: \["inception", "the matrix"]. If both "query" and "queries" are set, all are searched. ## `type` (type: `string`): Which kinds of results to keep: "all" (titles + people + companies), "titles" (movies/shows only, IMDb ids starting tt), or "people" (cast/crew only, ids starting nm). ## `maxItems` (type: `integer`): Maximum number of de-duplicated rows to return across all queries. NOTE: a single query returns a fixed ~8 results (the suggestion API has no pagination); to get more, add more terms to "queries". If maxItems exceeds what's available, the actor just returns what it found. ## `notionConnector` (type: `string`): Optional. Write each item as a page into your Notion when the run finishes. Authorize a Notion connector once in Settings → API & Integrations → MCP connectors, then pick it here. Leave empty to skip (default) — results are always saved to the dataset regardless. ## `notionParentId` (type: `string`): Optional. The Notion data source ID of the database to write into (only used if a Notion connector is set). Leave empty to create the pages privately in your workspace instead. ## `proxyConfiguration` (type: `object`): OPTIONAL. IMDb's suggestion API is a public, no-auth JSON endpoint with no anti-bot, so no proxy is needed and the default routes traffic directly (saving proxy credits). Only enable Apify Proxy if you hit IP rate limits when running very high volumes. ## Actor input object example ```json { "query": "breaking bad", "queries": [], "type": "all", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `results` (type: `string`): Scraped rows are stored in the default dataset (one row per result). Blocked/empty/error runs return a single uncharged diagnostic row instead. # 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 = { "query": "breaking bad" }; // Run the Actor and wait for it to finish const run = await client.actor("dami_studio/imdb-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 = { "query": "breaking bad" } # Run the Actor and wait for it to finish run = client.actor("dami_studio/imdb-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 '{ "query": "breaking bad" }' | apify call dami_studio/imdb-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dami_studio/imdb-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "IMDb Search Scraper", "description": "Search IMDb for movies, TV shows and people using IMDb's own public suggestion API — no key, no login. Get clean rows with id, title/name, type, year, stars/known-for, poster image and the imdb.com URL. Pass multiple queries to fetch more.", "version": "0.1", "x-build-id": "Y0ZtM8tdfYmAle0He" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dami_studio~imdb-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dami_studio-imdb-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/dami_studio~imdb-scraper/runs": { "post": { "operationId": "runs-sync-dami_studio-imdb-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/dami_studio~imdb-scraper/run-sync": { "post": { "operationId": "run-sync-dami_studio-imdb-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": { "query": { "title": "Search query", "type": "string", "description": "A single thing to search IMDb for — a movie, TV show or person name, e.g. \"breaking bad\" or \"tom hanks\". For several searches at once, use the \"queries\" field below instead (or as well)." }, "queries": { "title": "Multiple queries", "type": "array", "description": "Run several searches in one go — one request per term, results merged and de-duplicated by IMDb id. Use this to get more than the ~8 results a single query returns (the suggestion API has no pagination). Example: [\"inception\", \"the matrix\"]. If both \"query\" and \"queries\" are set, all are searched.", "default": [], "items": { "type": "string" } }, "type": { "title": "Result type", "enum": [ "all", "titles", "people" ], "type": "string", "description": "Which kinds of results to keep: \"all\" (titles + people + companies), \"titles\" (movies/shows only, IMDb ids starting tt), or \"people\" (cast/crew only, ids starting nm).", "default": "all" }, "maxItems": { "title": "Max results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of de-duplicated rows to return across all queries. NOTE: a single query returns a fixed ~8 results (the suggestion API has no pagination); to get more, add more terms to \"queries\". If maxItems exceeds what's available, the actor just returns what it found.", "default": 50 }, "notionConnector": { "title": "Notion connector (optional)", "type": "string", "description": "Optional. Write each item as a page into your Notion when the run finishes. Authorize a Notion connector once in Settings → API & Integrations → MCP connectors, then pick it here. Leave empty to skip (default) — results are always saved to the dataset regardless." }, "notionParentId": { "title": "Notion target data source ID", "type": "string", "description": "Optional. The Notion data source ID of the database to write into (only used if a Notion connector is set). Leave empty to create the pages privately in your workspace instead." }, "proxyConfiguration": { "title": "Proxy (optional)", "type": "object", "description": "OPTIONAL. IMDb's suggestion API is a public, no-auth JSON endpoint with no anti-bot, so no proxy is needed and the default routes traffic directly (saving proxy credits). Only enable Apify Proxy if you hit IP rate limits when running very high volumes.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```