# FDA Regulatory Scraper (`comfy_glove/fda-regulatory-consultant-scraper`) Actor Scrapes FDA regulatory consulting firms from USASpending.gov with urgency scoring to identify firms ready for new client engagements. - **URL**: https://apify.com/comfy\_glove/fda-regulatory-consultant-scraper.md - **Developed by:** [Zsombor Szekeres](https://apify.com/comfy_glove) (community) - **Categories:** Automation, Lead generation - **Stats:** 2 total users, 2 monthly users, 92.3% runs succeeded, NaN bookmarks - **User rating**: 5.00 out of 5 stars ## 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 ## FDA Regulatory Scraper The FDA Regulatory Scraper is an Apify Actor that scrapes and scores FDA regulatory consulting firms from USASpending.gov — the official US federal spending database. It identifies companies that have been awarded contracts by the Food and Drug Administration in scientific, technical, and regulatory consulting categories. This actor is built for lead generation agencies targeting the FDA compliance space. Each result is enriched with a proprietary urgency score that surfaces firms most likely to be available for new client engagements — prioritizing consultants whose contracts are ending soon or have recently expired over firms that are fully booked mid-contract. ### What you get per lead - Company name and location - Industry / NAICS classification - Contract description - Award amount - Contract type and dates - Urgency score (0–100) and label: `ready_now`, `warming_up`, `pipeline`, or `low` ### Input options - Set how many leads you want - Filter by contract description keywords (e.g. CGMP, CDRH, validation) - Filter by NAICS codes - Set a minimum award amount to target established firms only - Set a minimum urgency score to only return high-priority leads - Sort by urgency, award amount, or contract end date ### Data source USASpending.gov public API — no API key required, always up to date, directly from the US government. ### Who is this for? Ideal for: Lead gen agencies, CROs, eQMS vendors, staffing firms, and anyone selling services to the FDA regulatory consulting market. ### Target website USASpending.gov # Actor input Schema ## `maxLeads` (type: `integer`): Maximum number of leads to scrape. ## `descriptionKeywords` (type: `array`): Filter contracts whose description contains at least one of these keywords. Leave empty to return all. ## `naicsCodes` (type: `array`): Industry codes to filter by. Defaults cover scientific/technical consulting, testing labs, biotech R&D, and management consulting. ## `minAwardAmount` (type: `integer`): Only include contracts above this dollar value. ## `minUrgencyScore` (type: `integer`): Only return leads at or above this urgency score. Use 70 for ready_now, 50 for warming_up, 30 for pipeline. ## `sortBy` (type: `string`): How to sort the final results. ## Actor input object example ```json { "maxLeads": 50, "descriptionKeywords": [ "regulatory", "compliance", "CGMP", "CDRH", "CDER", "device", "drug", "pharmaceutical", "validation" ], "naicsCodes": [ "541690", "541380", "541714", "541611" ], "minAwardAmount": 0, "minUrgencyScore": 0, "sortBy": "urgency_score" } ```` # Actor output Schema ## `company_name` (type: `string`): Legal name of the FDA contractor / regulatory consulting firm. ## `industry` (type: `string`): Human-readable NAICS industry description. ## `naics_code` (type: `string`): 6-digit North American Industry Classification System code. ## `contract_description` (type: `string`): Official description of the work performed under the FDA contract. ## `award_amount` (type: `string`): Total dollar value of the contract award. ## `contract_award_type` (type: `string`): Type of contract instrument (e.g. Definitive Contract, Delivery Order, BPA Call, Purchase Order). ## `start_date` (type: `string`): Contract start date in YYYY-MM-DD format. ## `end_date` (type: `string`): Contract end date in YYYY-MM-DD format. ## `award_id` (type: `string`): Unique USASpending contract identifier. ## `city` (type: `string`): City where the company is registered. ## `state` (type: `string`): US state code where the company is registered (e.g. PA, NY, VA). ## `urgency_score` (type: `string`): Score from 0–100 indicating how likely the firm is ready for a new client engagement. Higher = more available. ## `urgency_label` (type: `string`): Urgency tier: ready\_now (≥70), warming\_up (≥50), pipeline (≥30), low (<30). # 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("comfy_glove/fda-regulatory-consultant-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 = {} # Run the Actor and wait for it to finish run = client.actor("comfy_glove/fda-regulatory-consultant-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 '{}' | apify call comfy_glove/fda-regulatory-consultant-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=comfy_glove/fda-regulatory-consultant-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FDA Regulatory Scraper", "description": "Scrapes FDA regulatory consulting firms from USASpending.gov with urgency scoring to identify firms ready for new client engagements.", "version": "1.0", "x-build-id": "nhPLdMDKwIJiy03ob" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/comfy_glove~fda-regulatory-consultant-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-comfy_glove-fda-regulatory-consultant-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/comfy_glove~fda-regulatory-consultant-scraper/runs": { "post": { "operationId": "runs-sync-comfy_glove-fda-regulatory-consultant-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/comfy_glove~fda-regulatory-consultant-scraper/run-sync": { "post": { "operationId": "run-sync-comfy_glove-fda-regulatory-consultant-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "maxLeads" ], "properties": { "maxLeads": { "title": "Max Leads", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of leads to scrape.", "default": 50 }, "descriptionKeywords": { "title": "Contract Description Keywords", "type": "array", "description": "Filter contracts whose description contains at least one of these keywords. Leave empty to return all.", "default": [ "regulatory", "compliance", "CGMP", "CDRH", "CDER", "device", "drug", "pharmaceutical", "validation" ], "items": { "type": "string" } }, "naicsCodes": { "title": "NAICS Codes", "type": "array", "description": "Industry codes to filter by. Defaults cover scientific/technical consulting, testing labs, biotech R&D, and management consulting.", "default": [ "541690", "541380", "541714", "541611" ], "items": { "type": "string" } }, "minAwardAmount": { "title": "Minimum Award Amount ($)", "minimum": 0, "type": "integer", "description": "Only include contracts above this dollar value.", "default": 0 }, "minUrgencyScore": { "title": "Minimum Urgency Score (0-100)", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only return leads at or above this urgency score. Use 70 for ready_now, 50 for warming_up, 30 for pipeline.", "default": 0 }, "sortBy": { "title": "Sort Results By", "enum": [ "urgency_score", "award_amount", "end_date" ], "type": "string", "description": "How to sort the final results.", "default": "urgency_score" } } }, "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 } } } } } } } } } } ```