# NIH RePORTER Grants Scraper (`wakey7dev/nih-reporter-grants`) Actor

Search & normalize NIH-funded research grants. Cleaned PI names, organization names, agency codes & spending categories. 2.9M+ projects, free API.

- **URL**: https://apify.com/wakey7dev/nih-reporter-grants.md
- **Developed by:** [Chris Wakefield](https://apify.com/wakey7dev) (community)
- **Categories:** Business, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

![Chris The Dev](https://raw.githubusercontent.com/chriswakefield87/appstore-screenshot-translator/main/assets/actor-banner.png)

## NIH RePORTER Grants Scraper

Search and normalize NIH-funded research grants from the **NIH RePORTER API** — the official database of all NIH-funded projects. Returns cleaned, enriched data with normalized PI names, organization names, agency/IC codes, and spending categories.

### Features

- 🔍 **Full-text search** across project titles, abstracts, PI names, or organization names
- 🧹 **Data normalization** — messy NIH data gets cleaned:
  - Agency abbreviations (NCI → "National Cancer Institute")
  - Activity codes (R01 → "Research Project Grant")
  - Organization names (abbreviation expansion, title-case)
  - PI names (extra spaces removed, consistent casing)
  - Spending categories (numeric codes → human-readable labels)
- 📊 **Flexible filtering** by fiscal year, agency/IC code, activity code
- 📄 **Three output formats**: Full dataset (JSON), summary table (text), run statistics
- 🆓 **No API key required** — NIH RePORTER is completely free and open

### Input

| Field | Type | Required | Description |
|---|---|---|---|
| `searchQuery` | string | ✅ | Search term (e.g., "immunotherapy", "CRISPR", "Alzheimer") |
| `searchField` | select | No | Where to search: all, projectTitle, abstract, piName, orgName (default: all) |
| `fiscalYears` | array | No | Filter by fiscal years (e.g., \[2024, 2025]) |
| `agencyCodes` | array | No | Filter by NIH agency/IC (e.g., \["NCI", "NIAID"]) |
| `activityCodes` | array | No | Filter by activity code (e.g., \["R01", "R21"]) |
| `sortField` | select | No | Sort by: project\_start\_date, award\_amount, \_score (default: project\_start\_date) |
| `sortOrder` | select | No | asc or desc (default: desc) |
| `maxResults` | integer | No | Max results 1-1000 (default: 50) |

### Example Input

```json
{
  "searchQuery": "immunotherapy cancer",
  "searchField": "abstract",
  "fiscalYears": [2024, 2025],
  "agencyCodes": ["NCI"],
  "maxResults": 25
}
```

### Example Output (Dataset Item)

```json
{
  "projectNumber": "1R01CA287654-01A1",
  "projectTitle": "Novel Immunotherapy Approaches for Metastatic Melanoma",
  "applicationId": 10567890,
  "fiscalYear": 2025,
  "organization": {
    "name": "JOHNS HOPKINS UNIVERSITY",
    "nameNormalized": "Johns Hopkins University",
    "city": "BALTIMORE",
    "state": "MD",
    "country": "UNITED STATES",
    "type": "10",
    "typeLabel": "Domestic Higher Education"
  },
  "principalInvestigators": [
    {
      "firstName": "Sarah",
      "lastName": "Chen",
      "fullName": "Sarah Chen",
      "isContact": true
    }
  ],
  "agencyAdmin": {
    "code": "NCI",
    "name": "National Cancer Institute"
  },
  "activityCode": "R01",
  "activityCodeLabel": "R01 — Research Project Grant",
  "awardAmount": 450000,
  "isActive": true,
  "spendingCategories": [
    {"code": 28, "label": "Cancer"},
    {"code": 220, "label": "Tumor Immunology"}
  ]
}
```

### Use Cases

- **Academic research offices** — track competitor grant portfolios and funding trends
- **Biotech & pharma** — competitive intelligence on NIH-funded academic research
- **Consulting firms** — market analysis of NIH funding by disease area, institution, or region
- **Nonprofits** — monitor the NIH funding landscape for advocacy and strategy
- **AI/ML researchers** — build datasets of NIH-funded projects for analysis

### Data Source

Data from the [NIH RePORTER API v2](https://api.reporter.nih.gov/), a free public API provided by the National Institutes of Health. Contains over 2.9 million funded projects dating back to 1985. No API key required.

# Actor input Schema

## `searchQuery` (type: `string`):

Search term to find NIH-funded projects (e.g., 'immunotherapy', 'Alzheimer', 'CRISPR')

## `searchField` (type: `string`):

Which field to search within

## `fiscalYears` (type: `array`):

Filter by fiscal years (e.g., 2024, 2025, 2026). Leave empty for all years.

## `agencyCodes` (type: `array`):

Filter by NIH agency/IC codes (e.g., NCI, NIAID, NHLBI). Leave empty for all agencies.

## `activityCodes` (type: `array`):

Filter by activity codes (e.g., R01, R21, P01, U01). Leave empty for all types.

## `sortField` (type: `string`):

Field to sort results by

## `sortOrder` (type: `string`):

Sort direction

## `maxResults` (type: `integer`):

Maximum number of results to return (1-1000)

## Actor input object example

```json
{
  "searchQuery": "immunotherapy",
  "searchField": "all",
  "fiscalYears": [],
  "agencyCodes": [],
  "activityCodes": [],
  "sortField": "project_start_date",
  "sortOrder": "desc",
  "maxResults": 50
}
```

# Actor output Schema

## `results` (type: `string`):

All normalized grant records as JSON array

## `summary` (type: `string`):

Human-readable formatted summary table

## `stats` (type: `string`):

Machine-readable run statistics (totals, agency breakdowns)

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchQuery": "immunotherapy",
    "fiscalYears": [],
    "agencyCodes": [],
    "activityCodes": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("wakey7dev/nih-reporter-grants").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchQuery": "immunotherapy",
    "fiscalYears": [],
    "agencyCodes": [],
    "activityCodes": [],
}

# Run the Actor and wait for it to finish
run = client.actor("wakey7dev/nih-reporter-grants").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 '{
  "searchQuery": "immunotherapy",
  "fiscalYears": [],
  "agencyCodes": [],
  "activityCodes": []
}' |
apify call wakey7dev/nih-reporter-grants --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=wakey7dev/nih-reporter-grants",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Gm1ZTZda29aGQj3fH/builds/rg6cpNW3msq8NJgjX/openapi.json