# Federal Award Intelligence — USAspending.gov (`nasasurfer/federal-award-intelligence`) Actor Search US federal contracts, grants, loans & IDVs from USAspending.gov. Three modes: award search, vendor intelligence (roll-up by recipient), and new-award monitoring (alerts on schedule). Clean JSON for GovCon leads, KYC/due diligence, competitive intel & AI agents. No API key needed. - **URL**: https://apify.com/nasasurfer/federal-award-intelligence.md - **Developed by:** [D J](https://apify.com/nasasurfer) (community) - **Categories:** AI, Lead generation, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 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 ## Federal Award Intelligence — USAspending.gov Search U.S. federal **contracts, grants, loans, IDVs, and direct payments** from the official [USAspending.gov](https://www.usaspending.gov) API and get back **clean, normalized, agent-ready JSON** — no API key, no anti-bot, public-domain data. Built for **GovCon lead generation, vendor due diligence / KYC, competitive intelligence, and grant prospecting** — and designed to be called directly by an AI agent over MCP. --- ### Quick start (works with zero configuration) Click **Run** with the defaults and you'll get the 100 largest federal **contracts** awarded in the **last 90 days**, sorted by dollar value. From there, narrow with: - **Award type** — contracts / grants / loans / IDVs / direct payments / other - **Keywords** — company name, technology, NAICS description, etc. - **Recipient name contains** — find every award to a specific vendor - **Minimum award amount** — focus on awards above a dollar threshold - **Look back (days)** or explicit **Start/End dates** - **Place of performance state** — e.g. `VA` ### Modes (this is the differentiator) - **Search** — normalized award records. The commodity baseline. - **Recipient profiles (vendor intelligence)** — rolls awards up by recipient: total won in the window, award count, agencies, and biggest award. This turns raw rows into a *decision* ("who are the top vendors winning DoD cyber work this quarter") — what a GovCon/BD or due-diligence buyer actually pays for. - **Monitor new awards** — on a schedule, returns **only awards not seen before** (deduped in a persistent store). Wire it to Slack/email for a new-award alert on a competitor or NAICS. Recurring value, not a one-shot dump. ### Output (per record) ```json { "award_id": "...", "recipient_name": "...", "award_amount": 1234567.0, "award_type": "DEFINITIVE CONTRACT", "contract_award_type": "...", "description": "...", "start_date": "2026-04-01", "end_date": "2027-03-31", "awarding_agency": "...", "awarding_sub_agency": "...", "funding_agency": "...", "usaspending_url": "https://www.usaspending.gov/award//", "recipient_id": "...", "source": "usaspending.gov", "retrieved_at": "2026-06-20T00:00:00.000Z" } ```` ### Use as an MCP tool (agent-native) Once published, Apify exposes this actor as an MCP tool automatically. Point any MCP client at: ``` https://mcp.apify.com?tools=/federal-award-intelligence ``` The input fields above become the tool's typed parameters, so an agent can call it autonomously ("find recent DoD cybersecurity contracts over $5M") and get structured records back. ### Recommended pricing Use **pay-per-result (PAY\_PER\_EVENT)** at **$0.003–$0.005 per award record**. Configure the price in the Apify Console under the actor's *Publication → Monetization* settings, then add a charge call in `src/main.js` after each `pushData`: `await Actor.charge({ eventName: 'award-record' });`. Do **not** ship it free — on the Store, free signals "hobby project." ### Store listing fields (fill these in — they drive discovery) - **seoTitle:** `USAspending Federal Contract & Grant Search API for AI Agents` - **seoDescription:** `Search US federal contracts, grants, loans & IDVs from USAspending.gov. Clean JSON for GovCon leads, vendor due diligence & competitive intel. No API key.` *** ### Deploy ```bash npm install -g apify-cli apify login ## from this folder: apify push ``` Then run from the Apify Console, the API, or on a schedule (e.g. daily monitoring for new awards to a competitor). ### Honest positioning note USAspending already has at least one solid incumbent actor on the Store, so treat this as a **scaffold and a quality/agent-native play**, not an empty field. Your edge is a cleaner normalized schema, MCP-first design, reliable zero-config defaults, and tight GovCon positioning. The same code structure (open API in → normalized records out) transfers 1:1 to a **less-crowded data source** if your density audit finds a better gap — swap the endpoint, the field map, and the normalization, and keep everything else. Data: USAspending.gov is public-domain U.S. Government work. # Actor input Schema ## `mode` (type: `string`): search = raw award records. recipient\_profile = roll awards up into vendor intelligence (who won the most, totals, agencies, biggest award). monitor = on scheduled runs, return only NEW awards since the last run (deduped) — for alerts. ## `awardType` (type: `string`): Which category of federal award to search. ## `keywords` (type: `array`): Optional free-text keywords (e.g. company name, technology, NAICS description). Leave empty to return all awards in the window. ## `recipientSearchText` (type: `string`): Optional. Narrow to awards whose recipient (vendor) name matches this text. ## `minAmount` (type: `integer`): Only return awards at or above this dollar value. 0 = no minimum. ## `daysBack` (type: `integer`): Rolling window ending today. Ignored if explicit Start/End dates are set. ## `startDate` (type: `string`): YYYY-MM-DD. Overrides 'Look back'. ## `endDate` (type: `string`): YYYY-MM-DD. Overrides 'Look back'. ## `naicsCodes` (type: `array`): Filter awards by NAICS code. Add one or more 6-digit codes e.g. 541512 for computer systems design. Leave empty for all codes. ## `placeOfPerformanceState` (type: `string`): Two-letter US state code (e.g. VA) to filter where the work is performed. ## `maxResults` (type: `integer`): Maximum number of award records to return. ## Actor input object example ```json { "mode": "search", "awardType": "contracts", "keywords": [], "recipientSearchText": "", "minAmount": 0, "daysBack": 90, "naicsCodes": [], "maxResults": 100 } ``` # 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 = { "keywords": [], "naicsCodes": [] }; // Run the Actor and wait for it to finish const run = await client.actor("nasasurfer/federal-award-intelligence").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 = { "keywords": [], "naicsCodes": [], } # Run the Actor and wait for it to finish run = client.actor("nasasurfer/federal-award-intelligence").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 '{ "keywords": [], "naicsCodes": [] }' | apify call nasasurfer/federal-award-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nasasurfer/federal-award-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Federal Award Intelligence — USAspending.gov", "description": "Search US federal contracts, grants, loans & IDVs from USAspending.gov. \n\nThree modes: award search, vendor intelligence (roll-up by recipient), and new-award monitoring (alerts on schedule). \n\nClean JSON for GovCon leads, KYC/due diligence, competitive intel & AI agents. No API key needed.", "version": "0.1", "x-build-id": "I4cdLzrUqzEMUPTVY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nasasurfer~federal-award-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nasasurfer-federal-award-intelligence", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nasasurfer~federal-award-intelligence/runs": { "post": { "operationId": "runs-sync-nasasurfer-federal-award-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nasasurfer~federal-award-intelligence/run-sync": { "post": { "operationId": "run-sync-nasasurfer-federal-award-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "awardType" ], "properties": { "mode": { "title": "Mode", "enum": [ "search", "recipient_profile", "monitor" ], "type": "string", "description": "search = raw award records. recipient_profile = roll awards up into vendor intelligence (who won the most, totals, agencies, biggest award). monitor = on scheduled runs, return only NEW awards since the last run (deduped) — for alerts.", "default": "search" }, "awardType": { "title": "Award type", "enum": [ "contracts", "idvs", "grants", "direct_payments", "loans", "other" ], "type": "string", "description": "Which category of federal award to search.", "default": "contracts" }, "keywords": { "title": "Keywords", "type": "array", "description": "Optional free-text keywords (e.g. company name, technology, NAICS description). Leave empty to return all awards in the window.", "default": [], "items": { "type": "string" } }, "recipientSearchText": { "title": "Recipient name contains", "type": "string", "description": "Optional. Narrow to awards whose recipient (vendor) name matches this text.", "default": "" }, "minAmount": { "title": "Minimum award amount (USD)", "minimum": 0, "type": "integer", "description": "Only return awards at or above this dollar value. 0 = no minimum.", "default": 0 }, "daysBack": { "title": "Look back (days)", "minimum": 1, "maximum": 3650, "type": "integer", "description": "Rolling window ending today. Ignored if explicit Start/End dates are set.", "default": 90 }, "startDate": { "title": "Start date (optional)", "type": "string", "description": "YYYY-MM-DD. Overrides 'Look back'." }, "endDate": { "title": "End date (optional)", "type": "string", "description": "YYYY-MM-DD. Overrides 'Look back'." }, "naicsCodes": { "title": "NAICS codes (optional)", "type": "array", "description": "Filter awards by NAICS code. Add one or more 6-digit codes e.g. 541512 for computer systems design. Leave empty for all codes.", "default": [], "items": { "type": "string" } }, "placeOfPerformanceState": { "title": "Place of performance state (optional)", "type": "string", "description": "Two-letter US state code (e.g. VA) to filter where the work is performed." }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of award records to return.", "default": 100 } } }, "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 } } } } } } } } } } ```