# Federal Register Rule & Notice Monitor – Regulatory Change API (`peepee/federal-register-rule-monitor`) Actor Real-time Federal Register feed of proposed/final rules, notices and presidential documents by agency, topic and docket. For regulatory-affairs, legal, and policy-intelligence teams. - **URL**: https://apify.com/peepee/federal-register-rule-monitor.md - **Developed by:** [K O](https://apify.com/peepee) (community) - **Categories:** Developer tools, 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.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 ## Federal Register Rule & Notice Monitor – Regulatory Change API A **Federal Register API** wrapper and regulatory-change monitor that pulls proposed and final rules, notices and presidential documents and normalizes each into a clean record: title, agency, document type, abstract, action, publication/effective dates, comment deadline and docket IDs. Use it to build a **regulatory-tracking tool**, a compliance early-warning system, or a policy-intelligence feed by agency or topic. ### Who uses it Regulatory-affairs and compliance teams, law firms, government-affairs and policy-intelligence firms, trade associations, and GovTech products. ### Why this is worth charging for Missing a comment deadline or a new rule affecting your industry is a real cost. The Federal Register API is excellent but returns verbose documents and paginates; this actor normalizes it into a deduplicated, topic- or agency-scoped feed with the dates that matter (effective, comments-close) surfaced, ready to schedule. ### Output Each dataset item is one normalized record: ```json { "documentNumber": "2024-12345", "title": "Air Quality Standards", "type": "Proposed Rule", "abstract": "The EPA proposes...", "action": "Proposed rule.", "agencies": [ "Environmental Protection Agency" ], "publicationDate": "2024-05-01", "commentsCloseDate": "2024-07-01", "docketIds": [ "EPA-HQ-OAR-2024-0001" ], "significant": true, "htmlUrl": "https://www.federalregister.gov/d/2024-12345", "source": "Federal Register" } ```` ### Input | Field | Description | |---|---| | `term` | Full-text term, e.g. 'per- and polyfluoroalkyl' or an industry keyword. | | `documentType` | Restrict to one document type. | | `agencySlug` | Agency slug, e.g. environmental-protection-agency. | | `publishedFrom` | Only include documents published on or after this date. | | `perPage` | Results per page (max 1000). | | `maxPagesToScan` | Pages per run. | | `onlyNewSinceLastRun` | Recommended for schedules — skips records already returned by a previous run using persisted state, so you're only charged for genuinely new items. | | `maxItems` | Stop after this many normalized records. | ### Pricing (Pay-Per-Event) - **`query`** — $0.01, charged once per run for the API query/poll. - **`document-record`** — $0.01 per normalized record pushed. This is the primary event. - `apify-actor-start` (Apify-managed) — covers baseline compute per run. A daily topic/agency monitor returns a handful of new documents, costing pennies. Broad historical pulls scale with pages scanned. ### Source & reliability Data comes from the official `federalregister.gov/api/v1` service. No API key or proxies required. Run `npm test` for the offline self-test covering the normalizer, including edge cases and missing-field handling. ### FAQ **Is there an API for the Federal Register?** Yes — this actor wraps it and returns clean, deduplicated document records with the key regulatory dates surfaced, via the Apify API, webhook or export. **Can I watch one agency?** Yes. Set agencySlug (and/or a term) and schedule with onlyNewSinceLastRun for agency-specific regulatory alerts. *** *SEO keywords: Federal Register API, regulatory tracking API, proposed rule monitor, rulemaking scraper, compliance alert feed, regulations.gov alternative* # Actor input Schema ## `term` (type: `string`): Full-text term, e.g. 'per- and polyfluoroalkyl' or an industry keyword. ## `documentType` (type: `string`): Restrict to one document type. ## `agencySlug` (type: `string`): Agency slug, e.g. environmental-protection-agency. ## `publishedFrom` (type: `string`): Only include documents published on or after this date. ## `perPage` (type: `integer`): Results per page (max 1000). ## `maxPagesToScan` (type: `integer`): Pages per run. ## `maxItems` (type: `integer`): Stop after this many normalized records have been pushed. Leave blank for no limit (bounded by pagination settings). ## `onlyNewSinceLastRun` (type: `boolean`): Recommended for scheduled runs. Uses persisted state to skip records already returned earlier, so a recurring schedule only charges for genuinely new items. ## Actor input object example ```json { "perPage": 100, "maxPagesToScan": 3, "onlyNewSinceLastRun": true } ``` # 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("peepee/federal-register-rule-monitor").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("peepee/federal-register-rule-monitor").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 peepee/federal-register-rule-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=peepee/federal-register-rule-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Federal Register Rule & Notice Monitor – Regulatory Change API", "description": "Real-time Federal Register feed of proposed/final rules, notices and presidential documents by agency, topic and docket. For regulatory-affairs, legal, and policy-intelligence teams.", "version": "1.0", "x-build-id": "2jZVdUt2Z3gS77eWM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/peepee~federal-register-rule-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-peepee-federal-register-rule-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/peepee~federal-register-rule-monitor/runs": { "post": { "operationId": "runs-sync-peepee-federal-register-rule-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/peepee~federal-register-rule-monitor/run-sync": { "post": { "operationId": "run-sync-peepee-federal-register-rule-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "term": { "title": "Search term", "type": "string", "description": "Full-text term, e.g. 'per- and polyfluoroalkyl' or an industry keyword." }, "documentType": { "title": "Document type", "enum": [ "RULE", "PRORULE", "NOTICE", "PRESDOCU" ], "type": "string", "description": "Restrict to one document type." }, "agencySlug": { "title": "Agency slug", "type": "string", "description": "Agency slug, e.g. environmental-protection-agency." }, "publishedFrom": { "title": "Published on/after (YYYY-MM-DD)", "type": "string", "description": "Only include documents published on or after this date." }, "perPage": { "title": "Per page", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Results per page (max 1000).", "default": 100 }, "maxPagesToScan": { "title": "Max pages to scan", "minimum": 1, "maximum": 100, "type": "integer", "description": "Pages per run.", "default": 3 }, "maxItems": { "title": "Maximum records to return", "minimum": 1, "type": "integer", "description": "Stop after this many normalized records have been pushed. Leave blank for no limit (bounded by pagination settings)." }, "onlyNewSinceLastRun": { "title": "Only return records not seen in a previous run", "type": "boolean", "description": "Recommended for scheduled runs. Uses persisted state to skip records already returned earlier, so a recurring schedule only charges for genuinely new items.", "default": true } } }, "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 } } } } } } } } } } ```