# USASpending Federal Awards Extractor (`xtracto/usaspending-awards`) Actor Extract US federal contract, grant, and loan awards from USASpending.gov — one award per row, with recipient, amount, agency, and dates. Public data, no key. - **URL**: https://apify.com/xtracto/usaspending-awards.md - **Developed by:** [Farhan Febrian Nauval](https://apify.com/xtracto) (community) - **Categories:** Lead generation, Other - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## USAspending Federal Awards Scraper Extract **US federal awards** — contracts, IDVs, grants, loans, and direct payments — from USAspending.gov, one **award per row**, with recipient, amount, awarding agency, type, and dates. Built for government-contracting (GovCon) business-development and capture teams, competitive-intelligence analysts, journalists, and anyone tracking federal spending. --- ### Why use this actor - **No account, no API key required.** - **One award per row**, with the source fields kept as-is — drops straight into a spend or BD model. - **Filter by award type, fiscal period, agency, and keyword** so you pull exactly what you need. - **Stable JSON output** ready for pipelines, CRMs, spreadsheets, or databases. ### How it works 1. You pick an **award type** (contracts, grants, loans…) and a **date window**. 2. *(Optional)* Narrow by **agency** or **keyword**. 3. The actor collects every matching award — recipient, amount, agency, type, dates — and streams it into your dataset, ready to download as JSON, CSV, or Excel. You don't manage any scrapers, accounts, or infrastructure — just set the filters and press **Run**. ### Use cases **Find who's winning contracts in your market** Pull contracts for a fiscal year filtered to a specific agency, sorted by amount, to map the incumbents and the size of each award. **Build a GovCon prospect & teaming list** Pull awards by keyword (your capability area) to surface prime recipients to target for teaming or subcontracting. **Track federal spending trends** Pull grants or direct payments across periods to chart how an agency's spending shifts year over year. ### Input | Field | Type | Description | | --- | --- | --- | | `awardGroup` | dropdown | Contracts / IDVs / Grants / Direct payments / Loans / Other. | | `timePeriodStart` / `timePeriodEnd` | string | Action-date window (YYYY-MM-DD). | | `keyword` | string | Optional free-text filter. | | `awardingAgencyNames` | list | Optional top-tier agency names, e.g. "Department of Defense". | | `maxItems` | integer | 0 = up to the per-query maximum. | `awardGroup` is a **pick-list** — it maps to the right award categories automatically. ### Output — one record per award ```json { "_input": "contracts 2024-10-01..2025-09-30", "_source": "S1-usaspending", "_scrapedAt": "2026-06-03T10:00:00Z", "recordType": "AWARD", "award_group": "contracts", "Award ID": "HT940216C0001", "Recipient Name": "HUMANA GOVERNMENT BUSINESS INC", "Award Amount": 51269205263.03, "Awarding Agency": "Department of Defense", "Award Type": "DEFINITIVE CONTRACT", "Start Date": "2025-01-15" } ```` | Field | Type | Description | | --- | --- | --- | | `Recipient Name` | string | Who received the award. | | `Award Amount` | number | Dollar value. | | `Awarding Agency` | string | The federal agency. | | `Award Type` | string | Contract/grant/loan subtype. | ### Tip for very large pulls A single query returns up to ~10,000 awards. To pull more, **narrow the query** — a shorter date window, one agency, or a keyword — and run per slice. The run log tells you when you've hit the maximum. ### Known limits - Public government data — no account needed. - Verified live: FY2025 contracts and grants returned in full with paging confirmed. # Actor input Schema ## `awardGroup` (type: `string`): Which federal award type to pull. ## `timePeriodStart` (type: `string`): Action-date window start. ## `timePeriodEnd` (type: `string`): Action-date window end. ## `keyword` (type: `string`): Free-text keyword filter (recipient, description…). ## `awardingAgencyNames` (type: `array`): Top-tier agency names, e.g. 'Department of Defense'. Narrows the query (and helps beat the 10,000-row cap). ## `maxItems` (type: `integer`): Maximum records to return (0 = all matching). ## `proxyConfiguration` (type: `object`): Not required (public API). ## Actor input object example ```json { "awardGroup": "contracts", "timePeriodStart": "2024-10-01", "timePeriodEnd": "2025-09-30", "keyword": "", "awardingAgencyNames": [], "maxItems": 0, "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "timePeriodStart": "2024-10-01", "timePeriodEnd": "2025-09-30", "keyword": "", "awardingAgencyNames": [] }; // Run the Actor and wait for it to finish const run = await client.actor("xtracto/usaspending-awards").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 = { "timePeriodStart": "2024-10-01", "timePeriodEnd": "2025-09-30", "keyword": "", "awardingAgencyNames": [], } # Run the Actor and wait for it to finish run = client.actor("xtracto/usaspending-awards").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 '{ "timePeriodStart": "2024-10-01", "timePeriodEnd": "2025-09-30", "keyword": "", "awardingAgencyNames": [] }' | apify call xtracto/usaspending-awards --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=xtracto/usaspending-awards", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "USASpending Federal Awards Extractor", "description": "Extract US federal contract, grant, and loan awards from USASpending.gov — one award per row, with recipient, amount, agency, and dates. Public data, no key.", "version": "0.1", "x-build-id": "YhGziqaSObg1E6dP7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/xtracto~usaspending-awards/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-xtracto-usaspending-awards", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/xtracto~usaspending-awards/runs": { "post": { "operationId": "runs-sync-xtracto-usaspending-awards", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/xtracto~usaspending-awards/run-sync": { "post": { "operationId": "run-sync-xtracto-usaspending-awards", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "awardGroup" ], "properties": { "awardGroup": { "title": "Award type", "enum": [ "contracts", "idvs", "grants", "direct_payments", "loans", "other" ], "type": "string", "description": "Which federal award type to pull.", "default": "contracts" }, "timePeriodStart": { "title": "Period start (YYYY-MM-DD)", "type": "string", "description": "Action-date window start.", "default": "2024-10-01" }, "timePeriodEnd": { "title": "Period end (YYYY-MM-DD)", "type": "string", "description": "Action-date window end.", "default": "2025-09-30" }, "keyword": { "title": "Keyword (optional)", "type": "string", "description": "Free-text keyword filter (recipient, description…).", "default": "" }, "awardingAgencyNames": { "title": "Awarding agencies (optional)", "type": "array", "description": "Top-tier agency names, e.g. 'Department of Defense'. Narrows the query (and helps beat the 10,000-row cap).", "items": { "type": "string" } }, "maxItems": { "title": "Max awards (0 = up to the 10,000 cap)", "minimum": 0, "type": "integer", "description": "Maximum records to return (0 = all matching).", "default": 0 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Not required (public API).", "default": { "useApifyProxy": 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 } } } } } } } } } } ```