# Nces K12 School Leads Scraper (`gocreative.ai/nces-k12-school-leads`) Actor Scrape every US public K-12 school from NCES Common Core of Data. Get school name, district, address, phone, grade range, enrollment, and school type. Perfect for EdTech vendors, curriculum publishers, and school supply companies. - **URL**: https://apify.com/gocreative.ai/nces-k12-school-leads.md - **Developed by:** [GoCreative AI](https://apify.com/gocreative.ai) (community) - **Categories:** Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 33.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $6.00 / 1,000 leads 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## NCES K-12 School and District Leads ### 📊 Example output (real run) ![Sample output](https://api.apify.com/v2/key-value-stores/1ztQFHwG8acESTazI/records/nces-k12-school-leads-sample) A real record from a live run — clean structured data, exported as CSV / JSON / Excel or via API. Scrape public K-12 school contact data from NCES via the Urban Institute Education Data API. No API key required. ### Fields ncesId, schoolName, districtName, districtId, street, city, state, zip, phone, website, gradeLow, gradeHigh, schoolLevel, schoolType, enrollment, latitude, longitude ### Use cases - EdTech vendors prospecting by grade level and enrollment - Curriculum publishers targeting elementary/middle/high - School supply companies geo-targeting by state - Staffing agencies building district contact lists ### Pricing Pay Per Result - $0.01 per school record. ### Use cases - **B2B lead generation** — build targeted prospect lists with verified, structured data - **Sales prospecting** — find organizations and contacts that match your ICP - **Market research & competitive intelligence** — track this niche in structured form - **AI agents & automation** — feed agents clean external data without scraping infra - **Data enrichment** — append fresh fields to your existing lists ### Why use this actor - **Direct from the official source** — no stale third-party resale data - **Structured, typed output** — ready for CSV, JSON, Excel, or API export - **Pay-per-result** — no subscription, no minimums, only pay for data you get - **Schedulable** — run it once or set an Apify Schedule for fresh data on autopilot ### How it works This actor pulls data directly from the source, structures it into clean rows, and pushes each result to the dataset. It runs on Apify's infrastructure — reliable, schedulable, and pay-per-result so you only pay for data you actually get. ### FAQ **Do I need an API key or account?** No. Just provide your input and run it. **Can I schedule it to run automatically?** Yes — use Apify Schedules to run it hourly, daily, or weekly and get fresh data on autopilot. **What formats can I export?** CSV, JSON, Excel, or via the Apify API. **Can I integrate it into my own app?** Yes — call it via the Apify API and pull results directly into your pipeline. **Is the data accurate and fresh?** Data is pulled live from the source on each run, so it reflects what's available at run time. # Actor input Schema ## `state` (type: `string`): Two-letter US state abbreviation (e.g. CA, TX, NY, FL). ## `schoolLevel` (type: `string`): Filter: Elementary, Middle, High, or blank for all. ## `minEnrollment` (type: `integer`): Only include schools with at least this many students. 0 = all. ## `maxResults` (type: `integer`): Maximum school records to return (1-2000). ## Actor input object example ```json { "state": "CA", "schoolLevel": "", "minEnrollment": 0, "maxResults": 200 } ```` # Actor output Schema # 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 = { "state": "CA" }; // Run the Actor and wait for it to finish const run = await client.actor("gocreative.ai/nces-k12-school-leads").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 = { "state": "CA" } # Run the Actor and wait for it to finish run = client.actor("gocreative.ai/nces-k12-school-leads").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 '{ "state": "CA" }' | apify call gocreative.ai/nces-k12-school-leads --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gocreative.ai/nces-k12-school-leads", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Nces K12 School Leads Scraper", "description": "Scrape every US public K-12 school from NCES Common Core of Data. Get school name, district, address, phone, grade range, enrollment, and school type. Perfect for EdTech vendors, curriculum publishers, and school supply companies.", "version": "0.1", "x-build-id": "4z0GdnOTMkkeEnWcz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gocreative.ai~nces-k12-school-leads/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gocreative.ai-nces-k12-school-leads", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gocreative.ai~nces-k12-school-leads/runs": { "post": { "operationId": "runs-sync-gocreative.ai-nces-k12-school-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gocreative.ai~nces-k12-school-leads/run-sync": { "post": { "operationId": "run-sync-gocreative.ai-nces-k12-school-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "state": { "title": "State Abbreviation", "type": "string", "description": "Two-letter US state abbreviation (e.g. CA, TX, NY, FL).", "default": "CA" }, "schoolLevel": { "title": "School Level Filter", "type": "string", "description": "Filter: Elementary, Middle, High, or blank for all.", "default": "" }, "minEnrollment": { "title": "Minimum Enrollment", "minimum": 0, "type": "integer", "description": "Only include schools with at least this many students. 0 = all.", "default": 0 }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Maximum school records to return (1-2000).", "default": 200 } } }, "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 } } } } } } } } } } ```