# PatentsView — USPTO Patent Search & Analytics (`commonelements/patentsview-search`) Actor Search and download US patent data from the USPTO PatentsView API. Filter by keyword, assignee, inventor, patent type, date, and CPC classification. Returns titles, abstracts, assignees, and inventors. No API key required. - **URL**: https://apify.com/commonelements/patentsview-search.md - **Developed by:** [Harry Schoeller](https://apify.com/commonelements) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $1.00 / 1,000 dataset item scrapeds 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 ## PatentsView — USPTO Patent Search & Analytics Search and download US patent data from the USPTO PatentsView API. Covers 8+ million utility, design, and plant patents dating back to 1976. ### Example input — AI patents from big tech ```json { "searchTerm": "large language model", "startDate": "2022-01-01", "endDate": "2024-12-31", "maxRecords": 500 } ```` ### Filter by assignee (company) ```json { "assignee": "Apple Inc", "startDate": "2023-01-01", "maxRecords": 200 } ``` ### Example output record ```json { "patentNumber": "11234567", "patentTitle": "System and method for natural language processing", "patentDate": "2023-02-14", "patentType": "utility", "abstract": "A system for processing natural language inputs...", "assignees": ["OpenAI LLC"], "assigneeCountry": "US", "inventors": ["Altman, Samuel H.", "Brockman, Gregory"], "cpcCodes": ["G06N3/04", "G06F40/30"], "fetchedAt": "2025-01-01T00:00:00.000Z" } ``` ### CPC classification search ```json { "cpcCode": "G06N", "startDate": "2023-01-01", "maxRecords": 500 } ``` Common CPC codes: `G06N` (AI/ML), `A61K` (pharmaceuticals), `H04L` (networking), `B60` (vehicles), `G06F` (computing) ### Use cases - IP competitive intelligence and patent landscaping - Technology trend analysis - Freedom-to-operate research - M\&A due diligence and IP valuation - Academic innovation research # Actor input Schema ## `searchTerm` (type: `string`): Keyword(s) to search within patent titles. Any matching word will be included. Example: 'artificial intelligence', 'neural network'. ## `assignee` (type: `string`): Filter by the organization or company that owns the patent. Any matching word will be included. Example: 'Google', 'IBM', 'Massachusetts Institute of Technology'. ## `inventorLastName` (type: `string`): Filter by inventor's last name (exact match). Example: 'Smith', 'Chen'. ## `patentType` (type: `string`): Filter by patent type. Leave empty to include all types. ## `startDate` (type: `string`): Include patents issued on or after this date. Format: YYYY-MM-DD. Example: '2020-01-01'. ## `endDate` (type: `string`): Include patents issued on or before this date. Format: YYYY-MM-DD. Example: '2024-12-31'. ## `cpcCode` (type: `string`): Filter by CPC (Cooperative Patent Classification) subgroup ID prefix. Example: 'G06N' for AI/neural networks, 'H04L' for transmission of digital information. ## `maxRecords` (type: `integer`): Maximum number of patents to return. The API caps at 10,000 total per query. Set to 0 for no limit (up to 10,000). ## Actor input object example ```json { "searchTerm": "neural network", "assignee": "Google", "inventorLastName": "Smith", "patentType": "utility", "startDate": "2023-01-01", "endDate": "2024-01-01", "cpcCode": "G06N", "maxRecords": 100 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("commonelements/patentsview-search").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("commonelements/patentsview-search").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 commonelements/patentsview-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=commonelements/patentsview-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PatentsView — USPTO Patent Search & Analytics", "description": "Search and download US patent data from the USPTO PatentsView API. Filter by keyword, assignee, inventor, patent type, date, and CPC classification. Returns titles, abstracts, assignees, and inventors. No API key required.", "version": "0.1", "x-build-id": "OS3LLXk5UKnisAHgZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/commonelements~patentsview-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-commonelements-patentsview-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/commonelements~patentsview-search/runs": { "post": { "operationId": "runs-sync-commonelements-patentsview-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/commonelements~patentsview-search/run-sync": { "post": { "operationId": "run-sync-commonelements-patentsview-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerm": { "title": "Search term (patent title)", "type": "string", "description": "Keyword(s) to search within patent titles. Any matching word will be included. Example: 'artificial intelligence', 'neural network'." }, "assignee": { "title": "Assignee (company / organization)", "type": "string", "description": "Filter by the organization or company that owns the patent. Any matching word will be included. Example: 'Google', 'IBM', 'Massachusetts Institute of Technology'." }, "inventorLastName": { "title": "Inventor last name", "type": "string", "description": "Filter by inventor's last name (exact match). Example: 'Smith', 'Chen'." }, "patentType": { "title": "Patent type", "enum": [ "utility", "design", "plant", "reissue" ], "type": "string", "description": "Filter by patent type. Leave empty to include all types." }, "startDate": { "title": "Start date (YYYY-MM-DD)", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Include patents issued on or after this date. Format: YYYY-MM-DD. Example: '2020-01-01'." }, "endDate": { "title": "End date (YYYY-MM-DD)", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Include patents issued on or before this date. Format: YYYY-MM-DD. Example: '2024-12-31'." }, "cpcCode": { "title": "CPC subgroup ID prefix", "type": "string", "description": "Filter by CPC (Cooperative Patent Classification) subgroup ID prefix. Example: 'G06N' for AI/neural networks, 'H04L' for transmission of digital information." }, "maxRecords": { "title": "Max records", "minimum": 0, "type": "integer", "description": "Maximum number of patents to return. The API caps at 10,000 total per query. Set to 0 for no limit (up to 10,000).", "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 } } } } } } } } } } ```