# Google Patents API (`johnvc/google-patents-api`) Actor Google Patents API for Claude, Cursor, ChatGPT, and any MCP-compatible AI agent. Search by keyword, inventor, or assignee across USPTO, EPO, WIPO, JPO, CN, KR + 100 offices. Pull claims, citations, family graphs, CPC. AI patent summaries. Pay per event. - **URL**: https://apify.com/johnvc/google-patents-api.md - **Developed by:** [John](https://apify.com/johnvc) (community) - **Categories:** AI, Integrations, MCP servers - **Stats:** 4 total users, 4 monthly users, 100.0% runs succeeded, 4 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.01 / 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 ## Google Patents MCP - Search, Details, Citations, AI Summaries > The Google Patents API for AI agents and IP professionals. Use this actor with Claude, Cursor, ChatGPT, or any MCP-compatible AI agent. Search Google Patents by keyword, inventor, or assignee across USPTO, EPO, WIPO, JPO, CN, KR, and 100+ patent offices. Pull full patent details: claims, citations, family graphs, CPC classifications, and PDF URLs. Get AI-generated patent summaries (top assignees, inventors, and CPC classes with percentage and year-range frequency). Pay per event - no flat monthly fees. ### Use it from your AI agent Wire this actor into Claude, Cursor, ChatGPT, or any MCP client and your agent can run tasks like: - "Find all patents filed by Apple in the last 5 years and return assignees, inventors, filing dates, and citation counts." - "Pull the full claims, abstract, and citation network for patent US10123456B2." - "Get an AI-generated summary of patents about graphene battery with the top assignees and CPC classes." - "Monitor new patents filed in CPC class H01M for any new applications since last month." - "Build a citation graph from patent US11734097B1 showing all backward and forward citations." - "Find all patents by inventor John Smith at IBM and rank by forward citation count." ### For IP attorneys, R&D teams, and patent valuation specialists This actor is built for professional patent work: - **Prior-art search** - Full keyword + filter search across 100+ offices with CPC/IPC classification filtering and date-range filtering on priority, filing, or publication dates. - **Freedom-to-operate analysis** - Pull full claims text and citation networks for any patent in seconds; export as JSON to feed into your claim-chart workflow. - **Technology landscaping** - The AI summary block returns top assignees and top CPC classes for any search, with year-range frequency arrays so you can visualize a technology landscape in one chart. - **Patent valuation** - Forward citation counts (cited_by) come back with every details lookup, ready to feed citation-weighted valuation models. - **Competitive intelligence** - byAssignee mode gives you every patent from a target company filtered to a country, type, status, and date range, in one call. ### Quick start #### Run as an MCP tool (Claude, Cursor, ChatGPT) Connect your AI agent to Apify's MCP server, then call this actor by its full name: ```` johnvc/google-patents-api ```` The actor's input schema is fully described with `title` and `description` fields on every parameter, so your agent can pick the right inputs on its own. #### Run from the Apify console 1. Click **Try for free** on the actor page. 2. Fill in a search query, e.g. `q: graphene battery`, `max_pages: 2`. 3. Click **Start**. Results land in the default dataset, one row per search page. #### Run via the Apify API ```bash curl -X POST "https://api.apify.com/v2/acts/johnvc~google-patents-api/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "q": "graphene battery", "country": "US,EP", "after": "filing:20200101", "max_pages": 3, "include_ai_summary": true }' ```` ### Input parameters The actor accepts one flat input form. The mode is implicit from which fields you fill: | Field | Type | Description | |---|---|---| | `q` | string | Free-text search query. At least one of q, patent\_id, assignee, or inventor is required. | | `patent_id` | string | Provide to fetch full details for a specific patent. Format `patent/US10123456B2/en` or `patent/US10123456B2`. | | `assignee` | string | Comma-separated assignee names (e.g. `Apple,Microsoft`). | | `inventor` | string | Comma-separated inventor names. | | `country` | string | Comma-separated patent office codes: US, EP, WO, JP, KR, CN, DE, GB, FR, CA, AU, IN, ... | | `language` | string | Comma-separated language codes: EN, DE, ZH, FR, ES, AR, JA, KO, PT, RU, IT, NL, SV, FI, NO, DA. | | `status` | enum | `GRANT` or `APPLICATION`. | | `type` | enum | `PATENT` or `DESIGN`. | | `before` / `after` | string | Date filters in the form `type:YYYYMMDD`, where type is `priority`, `filing`, or `publication`. | | `sort` | enum | `relevance`, `new`, `old`. | | `litigation` | enum | `YES` or `NO`. | | `num` | integer | Results per page (10 to 100, default 10). | | `max_pages` | integer | Number of pages to fetch (default 1, 0 for unlimited). | | `include_ai_summary` | boolean | Attach the AI summary block to the first page item. | | `include_details` | boolean | After pagination, also pull full details for each result up to 10 patents. | ### Output Each dataset item represents one page of search results (or one details record). The shape is: ```json { "search_parameters": { ... }, "search_metadata": { "total_results": 1340, "patents_count": 10, "pages_processed": 1, "mode": "search" }, "search_timestamp": "2026-05-14T12:34:56", "page_number": 1, "patents": [ { "patent_id": "patent/US10123456B2/en", "title": "...", "snippet": "...", "assignee": ["..."], "inventor": ["..."], "priority_date": "2018-01-15", "filing_date": "2019-01-15", "grant_date": "2021-11-23", "publication_date": "2021-11-23", "publication_number": "US10123456B2", "pdf": "https://patentimages.storage.googleapis.com/..." } ], "ai_summary": { "assignees": [{ "key": "...", "percentage": 12.4, "frequency": [...] }], "inventors": [...], "cpc": [...] } } ``` In details mode, the same item also carries a `details` object with `claims`, `cpc_classifications`, `patent_citations`, `non_patent_citations`, `cited_by`, `worldwide_applications`, parent/child/priority `applications`, `legal_events`, `images`, and the PDF URL. ### Pricing Pay per event: | Event | Price | |---|---| | Setup (per run) | $0.02 | | Page processed (one dataset item written) | $0.02 | A search page (~10 patents), a details lookup, and a details-mode result each count as one `page_processed`. Use `max_pages` and `include_details` to control your total spend. ### Scheduled monitoring To monitor new filings, schedule this actor in the Apify console and pair it with the `after: publication:YYYYMMDD` parameter. Each run returns only patents published after your cursor date - feed the dataset into your downstream alerting workflow. ### Support Issues or feature requests: open a ticket on the [Apify actor page](https://apify.com/johnvc/google-patents-api) or message the maintainer through the Apify console. *** Last Updated: 2026.05.19 # Actor input Schema ## `q` (type: `string`): Free-text search query (e.g., 'graphene battery', 'CRISPR gene editing'). At least one of: q, patent\_id, assignee, or inventor is required. ## `patent_id` (type: `string`): Provide to fetch full details for a specific patent instead of running a search. Format: 'patent/\/' (e.g., 'patent/US11734097B1/en') or 'patent/\'. ## `assignee` (type: `string`): Comma-separated assignee (company) names to filter results by (e.g., 'Apple,Microsoft'). Use alone or alongside q. ## `inventor` (type: `string`): Comma-separated inventor names to filter results by (e.g., 'John Smith,Jane Doe'). Use alone or alongside q. ## `country` (type: `string`): Comma-separated patent office codes. Common: US (USPTO), EP (EPO), WO (WIPO), JP (JPO), KR (KIPO), CN (CNIPA), DE, GB, FR, CA, AU, IN. Example: 'US,EP,WO'. ## `language` (type: `string`): Comma-separated languages. Use full names (ENGLISH, GERMAN, CHINESE, FRENCH, SPANISH, ARABIC, JAPANESE, KOREAN, PORTUGUESE, RUSSIAN, ITALIAN, DUTCH, SWEDISH, FINNISH, NORWEGIAN, DANISH) or 2-letter codes (EN, DE, ZH, ...) which we translate automatically. Example: 'ENGLISH,GERMAN' or 'EN,DE'. ## `status` (type: `string`): Filter by patent status. ## `type` (type: `string`): Filter by patent type. ## `before` (type: `string`): Upper-bound date filter. Format 'type:YYYYMMDD' where type is one of priority, filing, publication. Example: 'publication:20251231'. ## `after` (type: `string`): Lower-bound date filter. Format 'type:YYYYMMDD' where type is one of priority, filing, publication. Example: 'filing:20200101'. ## `sort` (type: `string`): Sort search results by relevance (default), newest first, or oldest first. ## `litigation` (type: `string`): Return only patents that have been litigated (YES) or only those that have not (NO). ## `num` (type: `integer`): Results returned per page, 10 to 100. Default 10. ## `max_pages` (type: `integer`): Maximum number of pages to fetch. Set to 0 for unlimited. Each page is one charged event. ## `clustered` (type: `boolean`): Group results by classification when true. ## `dups` (type: `boolean`): Collapse near-duplicate publications across languages so each unique invention shows once. ## `scholar` (type: `boolean`): Also include matching Google Scholar (academic paper) results alongside patents. Useful for prior-art workflows that consider non-patent literature. ## `no_cache` (type: `boolean`): Force a fresh fetch instead of returning cached results. Recommended for scheduled monitoring runs that need to detect newly published filings. ## `include_ai_summary` (type: `boolean`): Attach the AI-generated summary block (top assignees, inventors, CPC classes with percentages and year-range frequencies) to the first page item. Returned free with every search response. Default ON. No competitor offers this. ## `include_details` (type: `boolean`): After paginating, fetch full details (claims, citations, family, CPC, PDF URL) for each patent up to a hard cap of 10. Each details lookup is one additional charged event. ## Actor input object example ```json { "q": "semiconductor cooling", "num": 10, "max_pages": 1, "clustered": false, "dups": false, "scholar": false, "no_cache": false, "include_ai_summary": true, "include_details": false } ``` # Actor output Schema ## `results` (type: `string`): Full results from all pages and details lookups. Each dataset item contains search\_parameters, search\_metadata, page\_number, and either a patents array, a details object, or both. When include\_ai\_summary is true, an ai\_summary block is attached to the first page item. # 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 = { "q": "semiconductor cooling" }; // Run the Actor and wait for it to finish const run = await client.actor("johnvc/google-patents-api").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 = { "q": "semiconductor cooling" } # Run the Actor and wait for it to finish run = client.actor("johnvc/google-patents-api").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 '{ "q": "semiconductor cooling" }' | apify call johnvc/google-patents-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=johnvc/google-patents-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Patents API", "description": "Google Patents API for Claude, Cursor, ChatGPT, and any MCP-compatible AI agent. Search by keyword, inventor, or assignee across USPTO, EPO, WIPO, JPO, CN, KR + 100 offices. Pull claims, citations, family graphs, CPC. AI patent summaries. Pay per event.", "version": "0.0", "x-build-id": "xOpPEMoh2yQh0LA26" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/johnvc~google-patents-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-johnvc-google-patents-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/johnvc~google-patents-api/runs": { "post": { "operationId": "runs-sync-johnvc-google-patents-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/johnvc~google-patents-api/run-sync": { "post": { "operationId": "run-sync-johnvc-google-patents-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "q": { "title": "Search Query", "type": "string", "description": "Free-text search query (e.g., 'graphene battery', 'CRISPR gene editing'). At least one of: q, patent_id, assignee, or inventor is required." }, "patent_id": { "title": "Patent ID (details mode)", "type": "string", "description": "Provide to fetch full details for a specific patent instead of running a search. Format: 'patent//' (e.g., 'patent/US11734097B1/en') or 'patent/'." }, "assignee": { "title": "Assignee Filter", "type": "string", "description": "Comma-separated assignee (company) names to filter results by (e.g., 'Apple,Microsoft'). Use alone or alongside q." }, "inventor": { "title": "Inventor Filter", "type": "string", "description": "Comma-separated inventor names to filter results by (e.g., 'John Smith,Jane Doe'). Use alone or alongside q." }, "country": { "title": "Country / Patent Office", "type": "string", "description": "Comma-separated patent office codes. Common: US (USPTO), EP (EPO), WO (WIPO), JP (JPO), KR (KIPO), CN (CNIPA), DE, GB, FR, CA, AU, IN. Example: 'US,EP,WO'." }, "language": { "title": "Language", "type": "string", "description": "Comma-separated languages. Use full names (ENGLISH, GERMAN, CHINESE, FRENCH, SPANISH, ARABIC, JAPANESE, KOREAN, PORTUGUESE, RUSSIAN, ITALIAN, DUTCH, SWEDISH, FINNISH, NORWEGIAN, DANISH) or 2-letter codes (EN, DE, ZH, ...) which we translate automatically. Example: 'ENGLISH,GERMAN' or 'EN,DE'." }, "status": { "title": "Patent Status", "enum": [ "GRANT", "APPLICATION" ], "type": "string", "description": "Filter by patent status." }, "type": { "title": "Patent Type", "enum": [ "PATENT", "DESIGN" ], "type": "string", "description": "Filter by patent type." }, "before": { "title": "Latest Date Filter", "type": "string", "description": "Upper-bound date filter. Format 'type:YYYYMMDD' where type is one of priority, filing, publication. Example: 'publication:20251231'." }, "after": { "title": "Earliest Date Filter", "type": "string", "description": "Lower-bound date filter. Format 'type:YYYYMMDD' where type is one of priority, filing, publication. Example: 'filing:20200101'." }, "sort": { "title": "Sort Order", "enum": [ "relevance", "new", "old" ], "type": "string", "description": "Sort search results by relevance (default), newest first, or oldest first." }, "litigation": { "title": "Litigation Filter", "enum": [ "YES", "NO" ], "type": "string", "description": "Return only patents that have been litigated (YES) or only those that have not (NO)." }, "num": { "title": "Results per Page", "minimum": 10, "maximum": 100, "type": "integer", "description": "Results returned per page, 10 to 100. Default 10.", "default": 10 }, "max_pages": { "title": "Maximum Pages", "minimum": 0, "type": "integer", "description": "Maximum number of pages to fetch. Set to 0 for unlimited. Each page is one charged event.", "default": 1 }, "clustered": { "title": "Cluster by Classification", "type": "boolean", "description": "Group results by classification when true.", "default": false }, "dups": { "title": "Deduplicate by Publication", "type": "boolean", "description": "Collapse near-duplicate publications across languages so each unique invention shows once.", "default": false }, "scholar": { "title": "Include Google Scholar Results", "type": "boolean", "description": "Also include matching Google Scholar (academic paper) results alongside patents. Useful for prior-art workflows that consider non-patent literature.", "default": false }, "no_cache": { "title": "Bypass Cache", "type": "boolean", "description": "Force a fresh fetch instead of returning cached results. Recommended for scheduled monitoring runs that need to detect newly published filings.", "default": false }, "include_ai_summary": { "title": "Include AI Summary", "type": "boolean", "description": "Attach the AI-generated summary block (top assignees, inventors, CPC classes with percentages and year-range frequencies) to the first page item. Returned free with every search response. Default ON. No competitor offers this.", "default": true }, "include_details": { "title": "Include Full Details for Each Result", "type": "boolean", "description": "After paginating, fetch full details (claims, citations, family, CPC, PDF URL) for each patent up to a hard cap of 10. Each details lookup is one additional charged event.", "default": 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 } } } } } } } } } } ```