# Court Records Scraper: Case Law & Dockets (`scrapemint/court-records-scraper`) Actor Search US federal and state court records from CourtListener: case law opinions and court dockets by keyword, party, court and date. Get case name, court, dates, citation, citation count, judge, docket number and links. No API key. - **URL**: https://apify.com/scrapemint/court-records-scraper.md - **Developed by:** [Ken M](https://apify.com/scrapemint) (community) - **Categories:** Business, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Court Records Scraper: Case Law & Dockets Search US federal and state court records - published case law and court dockets - without a Westlaw or PACER bill. Built on [CourtListener](https://www.courtlistener.com) (by the non-profit Free Law Project), credited as the source. No API key, no login, no browser. ### Two record types **Case law (opinions)** - published court decisions. One row per case: - case name, court, jurisdiction - date filed and date argued - citation, neutral citation, and **how many times the case has been cited** (a strong signal of importance) - precedential status, docket number, judge, nature of suit - a text snippet and links to the opinion and its document **Dockets (filings)** - court case records. One row per docket: - case name, court, docket number - date filed and date terminated - assigned judge, nature of suit / cause, bankruptcy chapter - a link to the full docket ### Search and filter ```json { "queries": ["fair use copyright"], "recordType": "opinions", "sortBy": "most_cited" } ```` - **queries** - keywords, a party or company name, or a case name (one search per line) - **courts** - limit to specific courts by ID ("scotus" Supreme Court, "cafc" Federal Circuit, "ca9" 9th Circuit, "dcd" DC District) - **filedAfter / filedBefore** - date range - **sortBy** - best match, newest, oldest, or most cited ### Who uses this - **Law firms and paralegals**: research case law on an issue and pull dockets by party. - **Companies**: check litigation exposure and run due diligence on partners, suppliers and competitors by name. - **Legal researchers and journalists**: track cases and find the most-cited authorities on a topic. - **Law schools and students**: study case law and citation patterns with structured data. ### Pricing A small fee per record. Searches that match nothing are free note rows, and the first 2 rows of every run are free. ### Notes - Source: CourtListener / Free Law Project, a public database of US court opinions and dockets. Coverage is strongest for appellate and federal courts; docket coverage comes from the RECAP archive of PACER. - This returns the metadata and links for each record; full opinion text is linked from each row. # Actor input Schema ## `queries` (type: `array`): What to search for, one per line. Keywords ("fair use copyright"), a party or company name ("Google"), or a case name. Each runs its own search. ## `recordType` (type: `string`): Case law = published court opinions and decisions. Dockets = court case filings (parties, judge, docket number, dates). ## `courts` (type: `array`): Limit to specific courts by CourtListener court ID, one per line ("scotus" = Supreme Court, "cafc" = Federal Circuit, "ca9" = 9th Circuit, "dcd" = DC District). Leave empty for all courts. ## `filedAfter` (type: `string`): Only records filed on or after this date (YYYY-MM-DD). Leave empty for no lower bound. ## `filedBefore` (type: `string`): Only records filed on or before this date (YYYY-MM-DD). Leave empty for no upper bound. ## `sortBy` (type: `string`): Order of results. Most cited applies to case law only. ## `maxPerQuery` (type: `integer`): How many records to return per search. ## `maxRows` (type: `integer`): Stop after this many rows in total. ## Actor input object example ```json { "queries": [ "fair use copyright" ], "recordType": "opinions", "sortBy": "relevance", "maxPerQuery": 40, "maxRows": 1000 } ``` # 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 = { "queries": [ "fair use copyright" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapemint/court-records-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 = { "queries": ["fair use copyright"] } # Run the Actor and wait for it to finish run = client.actor("scrapemint/court-records-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 '{ "queries": [ "fair use copyright" ] }' | apify call scrapemint/court-records-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapemint/court-records-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Court Records Scraper: Case Law & Dockets", "description": "Search US federal and state court records from CourtListener: case law opinions and court dockets by keyword, party, court and date. Get case name, court, dates, citation, citation count, judge, docket number and links. No API key.", "version": "0.1", "x-build-id": "ocrHckOKWmLExgKVZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapemint~court-records-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapemint-court-records-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/scrapemint~court-records-scraper/runs": { "post": { "operationId": "runs-sync-scrapemint-court-records-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/scrapemint~court-records-scraper/run-sync": { "post": { "operationId": "run-sync-scrapemint-court-records-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": { "queries": { "title": "Search queries", "type": "array", "description": "What to search for, one per line. Keywords (\"fair use copyright\"), a party or company name (\"Google\"), or a case name. Each runs its own search.", "items": { "type": "string" } }, "recordType": { "title": "Record type", "enum": [ "opinions", "dockets" ], "type": "string", "description": "Case law = published court opinions and decisions. Dockets = court case filings (parties, judge, docket number, dates).", "default": "opinions" }, "courts": { "title": "Courts", "type": "array", "description": "Limit to specific courts by CourtListener court ID, one per line (\"scotus\" = Supreme Court, \"cafc\" = Federal Circuit, \"ca9\" = 9th Circuit, \"dcd\" = DC District). Leave empty for all courts.", "items": { "type": "string" } }, "filedAfter": { "title": "Filed after", "type": "string", "description": "Only records filed on or after this date (YYYY-MM-DD). Leave empty for no lower bound." }, "filedBefore": { "title": "Filed before", "type": "string", "description": "Only records filed on or before this date (YYYY-MM-DD). Leave empty for no upper bound." }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "newest", "oldest", "most_cited" ], "type": "string", "description": "Order of results. Most cited applies to case law only.", "default": "relevance" }, "maxPerQuery": { "title": "Results per query", "minimum": 1, "maximum": 2000, "type": "integer", "description": "How many records to return per search.", "default": 40 }, "maxRows": { "title": "Max rows", "minimum": 1, "maximum": 20000, "type": "integer", "description": "Stop after this many rows in total.", "default": 1000 } } }, "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 } } } } } } } } } } ```