# Scholarship Intel (`fiery_dream/scholarship-intel`) Actor Enterprise-grade scholarship, grants, and university intelligence platform. Features University Search: 6,400+ US institutions with detailed data Federal Grants: Real-time Grants.gov opportunities Education Spending: USAspending grant awards data and more! - **URL**: https://apify.com/fiery\_dream/scholarship-intel.md - **Developed by:** [Cody Churchwell](https://apify.com/fiery_dream) (community) - **Categories:** Other, Automation, Social media - **Stats:** 33 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 ## Grants & Scholarships Intelligence Enterprise-grade scholarship, grants, and university intelligence platform. ### Features - **University Search**: 6,400+ US institutions with detailed data - **Federal Grants**: Real-time Grants.gov opportunities - **Education Spending**: USAspending grant awards data - **Scholarship Matching**: 10+ scholarship categories - **Financial Aid Data**: Tuition, Pell grants, loan rates - **AI-Powered Analysis**: Personalized recommendations ### Data Sources (100% FREE, NO API KEY REQUIRED) | Source | Data Provided | |--------|---------------| | College Scorecard | University details, costs, outcomes | | Urban Institute | IPEDS educational data | | Opendatasoft | College locations, contact info | | Grants.gov | Federal grant opportunities | | USAspending | Education grant awards | | GDELT | Scholarship news monitoring | ### Input Parameters | Parameter | Type | Description | |-----------|------|-------------| | search_type | string | all, universities, grants, spending | | query | string | Search keyword | | state | string | 2-letter state code (CA, NY, TX) | | field_of_study | string | Academic field of interest | | degree_level | string | certificate/associate/bachelor/master/doctoral | | gpa | number | Student GPA (0.0-4.0) | | first_generation | boolean | First-gen student status | | include_ai_analysis | boolean | Enable AI recommendations | ### Scholarship Categories | Category | Description | |----------|-------------| | Merit-Based | Academic achievement, GPA, test scores | | Need-Based | FAFSA-determined financial need | | Athletic | NCAA/NAIA sports scholarships | | Minority | Underrepresented groups | | STEM | Science, Tech, Engineering, Math | | Arts | Visual/performing arts, humanities | | Military | Veterans, service members, dependents | | First-Generation | First in family to college | | Community Service | Volunteer/service record | | Study Abroad | International programs | ### Degree Levels | Code | Level | |------|-------| | 1 | Certificate (< 1 year) | | 2 | Certificate (1-2 years) | | 3 | Associate's Degree | | 4 | Bachelor's Degree | | 5 | Post-Baccalaureate Certificate | | 6 | Master's Degree | | 7 | Post-Master's Certificate | | 8 | Doctoral Degree | ### Output ```json { "timestamp": "2024-01-15T14:30:00Z", "search_type": "all", "query": "nursing", "state": "CA", "universities": [ { "name": "UCLA", "city": "Los Angeles", "state": "CA", "admission_rate": 0.14, "tuition_in_state": 13804, "tuition_out_of_state": 44830, "pell_grant_rate": 0.35, "median_earnings_10yr": 65000 } ], "federal_grants": [ { "title": "Nursing Education Grant", "agency": "HHS", "close_date": "2024-03-15", "award_ceiling": 500000 } ], "scholarship_types": [...], "report_text": "...", "ai_analysis": "Based on your profile..." } ```` ### Use Cases - **High School Students**: College search and scholarship matching - **Community College Students**: Transfer opportunities - **Graduate School Applicants**: Program and funding search - **First-Generation Students**: Financial aid guidance - **Career Changers**: Adult education options - **Financial Aid Offices**: Grant opportunity monitoring - **Education Researchers**: Institutional data analysis ### Example Usage ```bash ## Search universities in California apify call scholarship-intel -i '{ "search_type": "universities", "state": "CA", "field_of_study": "Computer Science" }' ## Find nursing scholarships apify call scholarship-intel -i '{ "query": "nursing", "degree_level": "bachelor", "gpa": 3.5, "include_ai_analysis": true }' ## Federal grants search apify call scholarship-intel -i '{ "search_type": "grants", "query": "STEM education" }' ``` ### Pricing Pay-per-event pricing: - $0.002 per scholarship report - AI analysis included when API key provided | Event | Price | |-------|-------| | scholarship-report | $0.002 | | Default dataset item | $0.00001 | ### Disclaimer This tool provides educational funding information for research purposes. Scholarship availability and requirements change frequently. Always verify information directly with institutions and funding organizations. # Actor input Schema ## `search_type` (type: `string`): What type of information to search for ## `query` (type: `string`): Search keyword (e.g., 'nursing', 'engineering', 'community college') ## `state` (type: `string`): Filter by US state (2-letter code, e.g., CA, NY, TX) ## `field_of_study` (type: `string`): Academic field of interest (e.g., Computer Science, Nursing, Business) ## `degree_level` (type: `string`): Target degree level ## `gpa` (type: `number`): Current or expected GPA (0.0 - 4.0) for scholarship matching ## `first_generation` (type: `boolean`): First in family to attend college (unlocks additional scholarships) ## `limit` (type: `integer`): Maximum number of results per category ## `include_ai_analysis` (type: `boolean`): Use AI to generate personalized recommendations (requires API key) ## `model_name` (type: `string`): LLM model for analysis ## `api_key` (type: `string`): API key for the selected AI model (Google AI Studio key for Gemini, OpenAI key for GPT, Anthropic key for Claude) ## Actor input object example ```json { "search_type": "all", "degree_level": "bachelor", "first_generation": false, "limit": 50, "include_ai_analysis": true, "model_name": "gemini/gemini-2.0-flash" } ``` # 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("fiery_dream/scholarship-intel").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("fiery_dream/scholarship-intel").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 fiery_dream/scholarship-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fiery_dream/scholarship-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Scholarship Intel", "description": "Enterprise-grade scholarship, grants, and university intelligence platform.\n\nFeatures\nUniversity Search: 6,400+ US institutions with detailed data\nFederal Grants: Real-time Grants.gov opportunities\nEducation Spending: USAspending grant awards data\nand more!", "version": "1.0", "x-build-id": "JSwiBp7ueXqQDB7Hf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fiery_dream~scholarship-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fiery_dream-scholarship-intel", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fiery_dream~scholarship-intel/runs": { "post": { "operationId": "runs-sync-fiery_dream-scholarship-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fiery_dream~scholarship-intel/run-sync": { "post": { "operationId": "run-sync-fiery_dream-scholarship-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "search_type": { "title": "Search Type", "enum": [ "all", "universities", "grants", "spending" ], "type": "string", "description": "What type of information to search for", "default": "all" }, "query": { "title": "Search Query", "type": "string", "description": "Search keyword (e.g., 'nursing', 'engineering', 'community college')" }, "state": { "title": "State", "pattern": "^[A-Z]{2}$", "type": "string", "description": "Filter by US state (2-letter code, e.g., CA, NY, TX)" }, "field_of_study": { "title": "Field of Study", "type": "string", "description": "Academic field of interest (e.g., Computer Science, Nursing, Business)" }, "degree_level": { "title": "Degree Level", "enum": [ "certificate", "associate", "bachelor", "master", "doctoral" ], "type": "string", "description": "Target degree level", "default": "bachelor" }, "gpa": { "title": "Student GPA", "minimum": 0, "maximum": 4, "type": "number", "description": "Current or expected GPA (0.0 - 4.0) for scholarship matching" }, "first_generation": { "title": "First-Generation Student", "type": "boolean", "description": "First in family to attend college (unlocks additional scholarships)", "default": false }, "limit": { "title": "Results Limit", "minimum": 10, "maximum": 100, "type": "integer", "description": "Maximum number of results per category", "default": 50 }, "include_ai_analysis": { "title": "Include AI Analysis", "type": "boolean", "description": "Use AI to generate personalized recommendations (requires API key)", "default": true }, "model_name": { "title": "AI Model", "enum": [ "gemini/gemini-2.0-flash", "gpt-4o-mini", "gpt-4o", "claude-3-5-sonnet-20241022" ], "type": "string", "description": "LLM model for analysis", "default": "gemini/gemini-2.0-flash" }, "api_key": { "title": "AI API Key", "type": "string", "description": "API key for the selected AI model (Google AI Studio key for Gemini, OpenAI key for GPT, Anthropic key for Claude)" } } }, "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 } } } } } } } } } } ```