# US Federal Spending & Contracts Search (`agentictools/federal-spending-search`) Actor Search US federal awards, contracts, and grants from USAspending by recipient, agency, or keyword. Amounts, recipients, and agencies. - **URL**: https://apify.com/agentictools/federal-spending-search.md - **Developed by:** [Ken Agland](https://apify.com/agentictools) (community) - **Categories:** Business, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $1.00 / 1,000 award returneds 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 ## US Federal Spending & Contracts Search Search US federal awards, contracts, and grants from USAspending by recipient, agency, or keyword. Get amounts, recipients, and agencies as clean structured data. This Actor queries the USAspending.gov award search API and returns normalized federal award records, sorted by award amount. ### Features - Search by one or more keywords matched against award descriptions and recipient names. - Filter to contracts, grants, or both. - Narrow to a specific recipient (company, university, state agency, and so on). - Results sorted by award amount, largest first. - Run summary with total awards returned, total dollar amount, and the top recipient by combined award value. ### Example input Largest AI-related federal contracts: ```json { "keywords": ["artificial intelligence"], "awardType": "contracts", "maxItems": 40 } ```` Grants to a specific university: ```json { "keywords": ["climate research"], "awardType": "grants", "recipient": "University of Texas", "maxItems": 25 } ``` ### Input | Field | Type | Description | |---|---|---| | `keywords` | array of strings | Search terms matched against award descriptions and recipient names. Required. | | `awardType` | string | `contracts`, `grants`, or `all`. Default `contracts`. | | `recipient` | string | Only keep awards where the recipient name matches this text. Leave empty for any recipient. | | `maxItems` | integer | How many awards to return, largest amount first. Default 40, max 1000. | ### Output Each dataset item is one federal award: ```json { "awardId": "W911QX20C0023", "recipient": "ECS FEDERAL, LLC", "amount": 120575059.35, "awardingAgency": "Department of Defense", "awardingSubAgency": "Department of the Army", "awardType": "contract", "startDate": "2020-04-23", "endDate": "2027-03-11", "description": "RESEARCH AND DEVELOPMENT EFFORT TO DESIGN AND DEVELOP PROTOTYPES TO ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ALGORITHMS.", "url": "https://www.usaspending.gov/award/CONT_AWD_W911QX20C0023_9700_-NONE-_-NONE-" } ``` #### Run summary (OUTPUT) The run's default key-value store record `OUTPUT` holds an aggregate for the whole result set: ```json { "query": { "keywords": ["artificial intelligence"], "awardType": "contracts", "recipient": null }, "itemsReturned": 40, "requestedMaxItems": 40, "totalAmount": 1834221904.12, "topRecipient": { "name": "ECS FEDERAL, LLC", "totalAmount": 188453416.55 }, "generatedFrom": "https://api.usaspending.gov/api/v2/search/spending_by_award/" } ``` ### How it works The Actor calls the public USAspending `spending_by_award` search API with your keywords, award type, recipient, and a wide time window covering all indexed awards. Contracts and grants use different award type codes that cannot be mixed in one request, so when `awardType` is `all` the Actor queries both groups and merges the results by amount. Pages are fetched until `maxItems` is reached or there are no more matches. No API key is required. ### Use cases - Find the largest federal contracts or grants in a given field or technology. - Track how much money a specific company or institution receives from the government. - Research an agency's spending on a topic before pitching a related product or service. - Feed federal award data into lead generation or market research pipelines. MIT licensed. # Actor input Schema ## `keywords` (type: `array`): Search terms matched against award descriptions and recipient names (for example a technology, product, or program name). Combine multiple terms for a broader search. ## `awardType` (type: `string`): Which kind of award to search: contracts, grants, or both. ## `recipient` (type: `string`): Only keep awards where the recipient name matches this text (for example a company or organization name). Leave empty for any recipient. ## `maxItems` (type: `integer`): How many awards to return. Results are paginated automatically until this count is reached or there are no more matches. ## Actor input object example ```json { "keywords": [ "cybersecurity" ], "awardType": "contracts", "recipient": "Booz Allen Hamilton", "maxItems": 40 } ``` # 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": [ "artificial intelligence" ] }; // Run the Actor and wait for it to finish const run = await client.actor("agentictools/federal-spending-search").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": ["artificial intelligence"] } # Run the Actor and wait for it to finish run = client.actor("agentictools/federal-spending-search").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": [ "artificial intelligence" ] }' | apify call agentictools/federal-spending-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentictools/federal-spending-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "US Federal Spending & Contracts Search", "description": "Search US federal awards, contracts, and grants from USAspending by recipient, agency, or keyword. Amounts, recipients, and agencies.", "version": "0.1", "x-build-id": "NPm6GdSzta8hY8i6m" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentictools~federal-spending-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentictools-federal-spending-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agentictools~federal-spending-search/runs": { "post": { "operationId": "runs-sync-agentictools-federal-spending-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agentictools~federal-spending-search/run-sync": { "post": { "operationId": "run-sync-agentictools-federal-spending-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "Search terms matched against award descriptions and recipient names (for example a technology, product, or program name). Combine multiple terms for a broader search.", "items": { "type": "string" } }, "awardType": { "title": "Award type", "enum": [ "contracts", "grants", "all" ], "type": "string", "description": "Which kind of award to search: contracts, grants, or both.", "default": "contracts" }, "recipient": { "title": "Recipient", "type": "string", "description": "Only keep awards where the recipient name matches this text (for example a company or organization name). Leave empty for any recipient." }, "maxItems": { "title": "Maximum items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "How many awards to return. Results are paginated automatically until this count is reached or there are no more matches.", "default": 40 } } }, "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 } } } } } } } } } } ```