# NEA Portfolio Report β€” Filtered VC Target Book (`nexgenwatch/nea-portfolio-report`) Actor Filtered, normalized target book of New Enterprise Associates' portfolio, with coverage stated and a source link per company. - **URL**: https://apify.com/nexgenwatch/nea-portfolio-report.md - **Developed by:** [NexGen Watch](https://apify.com/nexgenwatch) (community) - **Categories:** News, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 96.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $33.50 / 1,000 portfolio company records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## πŸ“ˆ NEA Portfolio Report β€” Filtered VC Target Book Build a **filtered, normalized target book of New Enterprise Associates' portfolio**, with a link to NEA's own page behind every single company. Built for deal sourcing, competitive mapping and BD teams who need a workable list instead of a wall of logos. Output is one `portfolio_company` row per result; billing is pay-per-event, the value event being one portfolio company record (a $0.02 start fee per run, then $0.05 per portfolio company record). Source: www.nea.com. No login, no API key and no CAPTCHA solving are involved: the source is read logged-out. **Who buys this** Buyers usually search for **NEA portfolio** or **VC portfolio companies**. - Sales and business-development teams prospecting the companies behind a NEA portfolio search. - Founders, investors and analysts mapping VC portfolio companies by sector and stage. - Market researchers building lists of venture-backed companies. ### πŸ“Š Sample Output [![NEA Portfolio Report β€” Filtered VC Target Book sample output β€” a table of real portfolio company record rows (slug, company_name, description, sectors) from run FFvghEh68ejZ1zhdK on build 0.1.31](https://api.apify.com/v2/key-value-stores/80Y7h3rmVN5CWK7Mw/records/nea-portfolio-report-sample-nw)](https://apify.com/nexgenwatch/nea-portfolio-report?fpr=2ayu9b) Real rows from run `FFvghEh68ejZ1zhdK` on build 0.1.31 (2026-09-28), the same input as the Quick start below β€” every value is as the source published it (emails masked, long text shortened): | slug | company_name | description | sectors | source_is | report_id | |---|---|---|---|---|---| | repros-therapeutics | Repros Therapeutics | Biopharmaceutical company developing therapeutic drugs and formulation | \["Healthcare", "Life Sciences"] | NEA's own published portfolio page for this company | 281f8567b4838704 | | radiology-partners | Radiology Partners | Provides a comprehensive professional radiology services solution deli | \["Healthcare", "Digital Health"] | NEA's own published portfolio page for this company | 281f8567b4838704 | | brenig | Brenig | Brenig is a small molecule drug development company that utilizes an A | \["Healthcare", "Life Sciences"] | NEA's own published portfolio page for this company | 281f8567b4838704 | | | | | | | 281f8567b4838704 | The run finished with the status message: `CAPPED: parsed=10/917 (1.1%); maxCompanies=10 bounded the sweep to the first 10 of 917 companies in the order NEA's sitemap lists them | matched=3 | coverage=10/917 complete=False | portfolio-company-record: delivered=3 ` ### βœ… What you get Each row is flat JSON with these fields (from the dataset schema and the sample run; a field the source does not publish for a given row is `null`): - `slug` (string/null) β€” e.g. `repros-therapeutics` - `company_name` (string/null) β€” e.g. `Repros Therapeutics` - `description` (string/null) β€” e.g. `Biopharmaceutical company developing therapeutic drugs and formulations designed` - `sectors` (array/null) β€” e.g. `["Healthcare", "Life Sciences"]` - `first_invested_year` (integer/null) β€” e.g. `2009` - `stage` (string/null) β€” e.g. `Public/PIPES` - `status` (string/null) β€” e.g. `IPO/Acquired` - `status_detail` (string/null) β€” e.g. `NASDAQ: RPRX (old) Acquired by Allergan` - `themes` (array/null) β€” e.g. `["AI"]` - `source_url` (string/null) β€” e.g. `https://www.nea.com/portfolio/repros-therapeutics` - `source_is` β€” e.g. `NEA's own published portfolio page for this company` - `record_type` (string) β€” e.g. `portfolio_company` - `report_id` (string) β€” e.g. `281f8567b4838704` - `generated_at` β€” e.g. `2026-09-28T04:21:51Z` - `firm` β€” e.g. `New Enterprise Associates (NEA)` - `source_of_record` β€” e.g. `https://www.nea.com/sitemap.xml` - `filter` β€” e.g. `{"sectors": ["Healthcare"], "stages": [], "statuses": [], "themes": [], "first_i` - `filter_is_active` β€” e.g. `True` - `universe_total` (integer/null) β€” e.g. `917` - `companies_examined` (integer/null) β€” e.g. `10` - `companies_unreadable` β€” e.g. `0` - `dead_sitemap_entries` β€” e.g. `0` - `coverage_complete` (boolean/null) β€” e.g. `False` - `coverage_pct` (number/null) β€” e.g. `1.1` - `coverage_caveat` (string/null) β€” e.g. `maxCompanies=10 bounded the sweep to the first 10 of 917 companies in the order ` - `match_count` (integer/null) β€” e.g. `3` - `terminal` (string/null) β€” e.g. `CAPPED` - `rate_limit_per_sec` β€” e.g. `2` - `requests_attempted` β€” e.g. `11` - `requests_failed` β€” e.g. `0` - `vocabularies_in_examined_set` β€” e.g. `{"sectors": {"Technology": 7, "Enterprise": 4, "Healthcare": 3, "Life Sciences":` - `no_match_is_an_answer` β€” null in every sample row - `nothing_is_inferred` β€” e.g. `status and stage are carried verbatim from NEA's own page for each company. This` - `report_markdown` β€” e.g. `# NEA portfolio β€” filtered target book **Generated** 2026-09-28T04:21:51Z **Firm` - `report_kv_key` β€” e.g. `PORTFOLIO_REPORT_281f8567b4838704` **βœ… What you get** - `slug` (string/null) β€” e.g. `repros-therapeutics` - `company_name` (string/null) β€” e.g. `Repros Therapeutics` - `description` (string/null) β€” e.g. `Biopharmaceutical company developing therapeutic drugs and formulations designed` - `sectors` (array/null) β€” e.g. `["Healthcare", "Life Sciences"]` - `first_invested_year` (integer/null) β€” e.g. `2009` - `stage` (string/null) β€” e.g. `Public/PIPES` - `status` (string/null) β€” e.g. `IPO/Acquired` - `status_detail` (string/null) β€” e.g. `NASDAQ: RPRX (old) Acquired by Allergan` - `themes` (array/null) β€” e.g. `["AI"]` - `source_url` (string/null) β€” e.g. `https://www.nea.com/portfolio/repros-therapeutics` - `source_is` β€” e.g. `NEA's own published portfolio page for this company` - `record_type` (string) β€” e.g. `portfolio_company` - `report_id` (string) β€” e.g. `77c504e96343071a` - `generated_at` β€” e.g. `2026-09-23T18:09:45Z` - `firm` β€” e.g. `New Enterprise Associates (NEA)` - `source_of_record` β€” e.g. `https://www.nea.com/sitemap.xml` - `filter` β€” e.g. `{"sectors": ["Healthcare"], "stages": [], "statuses": [], "themes": [], "first_i` - `filter_is_active` β€” e.g. `True` - `universe_total` (integer/null) β€” e.g. `917` - `companies_examined` (integer/null) β€” e.g. `10` - `companies_unreadable` β€” e.g. `0` - `dead_sitemap_entries` β€” e.g. `0` - `coverage_complete` (boolean/null) β€” e.g. `False` - `coverage_pct` (number/null) β€” e.g. `1.1` - `coverage_caveat` (string/null) β€” e.g. `maxCompanies=10 bounded the sweep to the first 10 of 917 companies in the order ` - `match_count` (integer/null) β€” e.g. `3` - `terminal` (string/null) β€” e.g. `CAPPED` - `rate_limit_per_sec` β€” e.g. `2` - `requests_attempted` β€” e.g. `11` - `requests_failed` β€” e.g. `0` - `vocabularies_in_examined_set` β€” e.g. `{"sectors": {"Technology": 7, "Enterprise": 4, "Healthcare": 3, "Life Sciences":` - `no_match_is_an_answer` β€” null in every sample row - `nothing_is_inferred` β€” e.g. `status and stage are carried verbatim from NEA's own page for each company. This` - `report_markdown` β€” e.g. `# NEA portfolio β€” filtered target book **Generated** 2026-09-23T18:09:45Z **Firm` - `report_kv_key` β€” e.g. `PORTFOLIO_REPORT_77c504e96343071a` **βœ… What you get** - `slug` (string/null) β€” e.g. `repros-therapeutics` - `company_name` (string/null) β€” e.g. `Repros Therapeutics` - `description` (string/null) β€” e.g. `Biopharmaceutical company developing therapeutic drugs and formulations designed` - `sectors` (array/null) β€” e.g. `["Healthcare", "Life Sciences"]` - `first_invested_year` (integer/null) β€” e.g. `2009` - `stage` (string/null) β€” e.g. `Public/PIPES` - `status` (string/null) β€” e.g. `IPO/Acquired` - `status_detail` (string/null) β€” e.g. `NASDAQ: RPRX (old) Acquired by Allergan` - `themes` (array/null) β€” e.g. `["AI"]` - `source_url` (string/null) β€” e.g. `https://www.nea.com/portfolio/repros-therapeutics` - `source_is` β€” e.g. `NEA's own published portfolio page for this company` - `record_type` (string) β€” e.g. `portfolio_company` - `report_id` (string) β€” e.g. `ef8b6207766db2a8` - `generated_at` β€” e.g. `2026-09-17T17:37:38Z` - `firm` β€” e.g. `New Enterprise Associates (NEA)` - `source_of_record` β€” e.g. `https://www.nea.com/sitemap.xml` - `filter` β€” e.g. `{"sectors": ["Healthcare"], "stages": [], "statuses": [], "themes": [], "first_i` - `filter_is_active` β€” e.g. `True` - `universe_total` (integer/null) β€” e.g. `917` - `companies_examined` (integer/null) β€” e.g. `10` - `companies_unreadable` β€” e.g. `0` - `dead_sitemap_entries` β€” e.g. `0` - `coverage_complete` (boolean/null) β€” e.g. `False` - `coverage_pct` (number/null) β€” e.g. `1.1` - `coverage_caveat` (string/null) β€” e.g. `maxCompanies=10 bounded the sweep to the first 10 of 917 companies in the order ` - `match_count` (integer/null) β€” e.g. `3` - `terminal` (string/null) β€” e.g. `CAPPED` - `rate_limit_per_sec` β€” e.g. `2` - `requests_attempted` β€” e.g. `11` - `requests_failed` β€” e.g. `0` - `vocabularies_in_examined_set` β€” e.g. `{"sectors": {"Technology": 7, "Enterprise": 4, "Healthcare": 3, "Life Sciences":` - `no_match_is_an_answer` β€” null in every sample row - `nothing_is_inferred` β€” e.g. `status and stage are carried verbatim from NEA's own page for each company. This` - `report_markdown` β€” e.g. `# NEA portfolio β€” filtered target book **Generated** 2026-09-17T17:37:38Z **Firm` - `report_kv_key` β€” e.g. `PORTFOLIO_REPORT_ef8b6207766db2a8` **Output** - one `portfolio_company` record per match β€” name, description, sectors, themes, first invested year, stage, status, status detail, and the NEA URL it came from - one `portfolio_report` record β€” the filter, the coverage numbers, the vocabularies - one `source_receipt` β€” terminal, HTTP statuses, request counts, pacing - a rendered markdown brief in the key-value store Every run also writes a `RUN_RECEIPT` record to its key-value store with the source checks it made and the counts it charged β€” diagnostics never land in the paid dataset. ### βš™οΈ Sample inputs **1. Quick start β€” the Store example (this is what the sample above came from)** ```json { "sectors": [ "Healthcare" ], "maxCompanies": 10 } ``` The sample run charged exactly: 1 Γ— $0.02 apify-actor-start + 3 Γ— $0.05 portfolio-company-record = **$0.17** on the Free tier β€” every delivered row was billed. This actor takes no size cap or filter beyond the input above, so the Store example is the one input to run; put it on a schedule to keep the data current. ### 🧾 JSON sample record One real record from run `FFvghEh68ejZ1zhdK`, exactly as it lands in the dataset (emails masked, long text shortened): ```json { "slug": "repros-therapeutics", "company_name": "Repros Therapeutics", "description": "Biopharmaceutical company developing therapeutic drugs and formulations designed to treat hormonal and reproductive system disorders.", "sectors": [ "Healthcare", "Life Sciences" ], "first_invested_year": 2009, "stage": "Public/PIPES", "status": "IPO/Acquired", "status_detail": "NASDAQ: RPRX (old) Acquired by Allergan", "themes": [], "source_url": "https://www.nea.com/portfolio/repros-therapeutics", "source_is": "NEA's own published portfolio page for this company", "record_type": "portfolio_company", "report_id": "281f8567b4838704" } ``` ### πŸ”§ How it works **Source.** The actor reads www.nea.com β€” endpoints: `https://www.nea.com/portfolio`, `https://www.nea.com/portfolio/`, `https://www.nea.com/sitemap.xml`. Public pages and feeds only; nothing behind a login. **Transport.** Plain HTTPS from the Apify platform, no proxy. robots.txt is read first and a disallowed path is never fetched. Pacing: `RATE_PER_SEC`=2.0, `MIN_INTERVAL`=1.0. **Terminal states.** A run ends NORMAL, CAPPED (your cap was reached), PARTIAL (something was withheld and the message says what), GENUINE_EMPTY (the source was read and truly had nothing in scope) or BLOCKED (the source refused or changed shape β€” the run FAILS loud and bills nothing). A zero-row run is never reported as a silent success. **Charging.** Each portfolio company record is charged at the moment it is pushed (`portfolio-company-record`); a row that fails to charge is not delivered, so the dataset count always equals the charged count. **πŸ”§ How it works** **πŸ”§ How it works** **Coverage is the headline, not the footnote** This actor sells a filtered book, so the worst thing it can do is hand you a short list that reads like a complete one. Every report states, in the record **and** on the first line of the brief: ``` universe_total 914 companies NEA publishes companies_examined 150 companies this run actually read coverage_complete false coverage_caveat "maxCompanies=150 bounded the sweep to the first 150 of 914 companies in sitemap order" ``` **A company missing from a partial book has not been ruled out β€” it was never read.** Raise `maxCompanies` toward 914 for a complete book; budget about a minute per 120 companies. Honouring your page budget perfectly still does not count as coverage. Coverage is measured against NEA's portfolio, not against the run's own limit. **1. `nea.com/portfolio` is not the portfolio** The page the phrase "scrape the portfolio" points at is a **30-logo featured carousel**. It carries no company name in text, no sector, no stage and no status β€” nothing to filter on. The universe comes from **the site's own declared sitemap**: 914 `/portfolio/` URLs out of 1,333, measured 2026-07-31. Each company's detail page carries the fields that make a target book: sectors, first-invested year, stage, company status and NEA's own one-line description. **2. Values must be sliced between labels, never by token offset** The detail page renders as a flat label/value stream: ``` Sectors | Technology | Enterprise | First Invested | 2014 | Early | Company Status | Private | Associated Team | ... | Theme | ... | Website ``` Two traps, both measured on real pages and both closed: - **A current holding has no status detail.** The token after the status is the *next label*. An offset parser reports every live company as `status_detail = "Associated Team"`. - **An exited company's block is the last one on the page.** `/portfolio/polyserve` has no team, theme or website section, so slicing "to the next label" ran the status detail into the site footer: *"Acquired by Hewlett Packard Β© NEA, 2026 Follow us on social media…"* β€” boilerplate glued onto a real field, on exactly the exited companies a buyer cares most about. Both are asserted against **verbatim excerpts of the live pages** in the test suite. **Nothing is inferred** `status` and `stage` are carried **verbatim** from NEA's page. This actor never decides that a company exited, failed, or is still held, and it never scores or ranks anyone. It reports what NEA publishes and links to it. NEA's published portfolio is the whole of this report. It is not a complete record of NEA's investments β€” a firm publishes what it chooses to. This is not investment advice. **Filters** | filter | what it does | |---|---| | `sectors` | keep companies tagged with any of these, e.g. Healthcare, Technology | | `themes` | keep companies tagged with any of these, e.g. AI, Infrastructure | | `stages` | stage at first investment, e.g. Seed, Early, Growth | | `statuses` | company status as NEA publishes it, e.g. Private, Acquired | | `firstInvestedFrom` / `firstInvestedTo` | year range of NEA's first investment | | `nameContains` | free text across company name and NEA's description | | `maxCompanies` | how much of the 914 to read β€” **default 150, a partial sweep** | Filtering runs here, over parsed fields, because the source offers no server-side filter at all. Every parameter therefore provably changes the result set, proven control-vs-test in the suite β€” none of them can be quietly discarded by the site. Each report also returns `vocabularies_in_examined_set`: the sectors, stages and statuses **counted from the companies this run actually read**, not from a hard-coded list. **Reading policy** `nea.com/robots.txt` reads `User-agent: * / Allow: /` with no crawl-delay. This actor paces itself at **2 requests/second** anyway, with a contact User-Agent. **The rate is not an input** β€” a buyer cannot dial it up. **What is not done.** No login, no cookie or CAPTCHA bypass, no private or personal-account data, no browser automation. ### πŸ’° Pricing example | Event | Free | Bronze | Silver | Gold | |---|---|---|---|---| | Actor Start (`apify-actor-start`) | $0.02 | $0.02 | $0.02 | $0.02 | | Portfolio company record (`portfolio-company-record`) | $0.05 | $0.045 | $0.04 | $0.0335 | Worked at the live Free-tier price: - 4 portfolio company records: $0.02 start + 4 Γ— $0.05 = **$0.22** - 25 portfolio company records: $0.02 start + 25 Γ— $0.05 = **$1.27** - 100 portfolio company records: $0.02 start + 100 Γ— $0.05 = **$5.02** A run that delivers zero rows charges the $0.02 start fee only. A BLOCKED run (source refused) fails loud and charges no value event. The start fee is charged once per GB of run memory; the default run memory is 512 MB. Yield on the sample run: `CAPPED: parsed=10/917 (1.1%); maxCompanies=10 bounded the sweep to the first 10 of 917 companies in the order NEA's sitemap lists them | matched=3 | coverage=10/917 complete=False | portfolio-company-`. ### βš–οΈ Legal & ToS This actor reads public, logged-out pages and feeds published by www.nea.com. It collects only what the source publishes to any visitor, keeps to the source's robots rules (checked on every run), identifies itself, and does not access accounts, private data or anything behind authentication. Use the output in line with the source's terms and your local law; the intended use is B2B research and monitoring. ### ❓ FAQ **Q: Do I need an API key or a login?**\ A: No. The source (www.nea.com) is read logged-out; the input schema has no key field and the actor carries no secrets. **Q: Why did my run return 0 rows?**\ A: Read the run's status message. GENUINE_EMPTY means the source was read and had nothing in scope for your input; BLOCKED means the source refused and the run failed without billing a value event β€” retry later or narrow the input. A zero-row run bills the start fee only. **Q: How fresh is the data?**\ A: Every run reads the source live at run time; nothing is cached between runs. Put it on a schedule for a continuous feed. **Q: What formats can I export?**\ A: The dataset downloads as JSON, CSV, Excel, XML or RSS from the run's Dataset tab or the Apify API, and any run can push to a webhook or integration. **Q: How is this different from the other VC portfolio reports actors?**\ A: Same output shape and billing model; this one covers www.nea.com. The siblings under **Related Actors** cover the other sources or slices β€” run several on one schedule for a combined feed. **Q: Are there rate limits?**\ A: The actor paces itself against the source (`RATE_PER_SEC`=2.0, `MIN_INTERVAL`=1.0) and honours its robots rules; there is no per-buyer limit beyond your Apify plan's concurrency. ### πŸ†˜ Troubleshooting - **Run FAILED with BLOCKED** β†’ the source refused the request or changed its page shape β†’ nothing was billed beyond the start fee; retry after a while, and if it persists open an Issue with the run id. - **Fewer rows than expected** β†’ the source had fewer items in scope β†’ widen the input. - **Input validation error on start** β†’ a field is outside the schema's allowed values β†’ start from the Quick start block and change one field at a time. - **Run TIMED-OUT** β†’ a very wide request on a slow day β†’ raise the run timeout in Run options or narrow the input; what was delivered before the timeout is still in the dataset. ### πŸ”— Related Actors - [General Atlantic Investments Report β€” Target Book](https://apify.com/nexgenwatch/general-atlantic-investments-report?fpr=2ayu9b) β€” Filtered, normalized target book of General Atlantic's published investments, with coverage stated and a source link per company - [USPTO Trademark Portfolio Report](https://apify.com/nexgenwatch/trademark-portfolio-report?fpr=2ayu9b) β€” One priced report that watches your whole trademark family for the two deadlines that cost clients marks: the 30-day opposition window and the Β§8/Β§9… - 🏒 **About NexGen Watch** β€” NexGen Watch is a catalog of more than 300 public data actors built on official sources, pay-per-result. Browse the catalog at [apify.com/nexgenwatch](https://apify.com/nexgenwatch?fpr=2ayu9b). ### ⭐ Found this useful? If this actor saved you a manual check, a quick **[review on the Apify Store](https://apify.com/nexgenwatch/nea-portfolio-report?fpr=2ayu9b)** helps other teams find it. Feature request or a source that changed? Open it from the **Issues** tab β€” every one is read. # Actor input Schema ## `sectors` (type: `array`): Keep only companies NEA tags with at least one of these sectors, e.g. Healthcare, Technology, Enterprise, Consumer, Life Sciences. Matching is case-insensitive. Leave empty for every sector. The exact vocabulary the run actually saw is reported back in vocabularies_in_examined_set. ## `themes` (type: `array`): Keep only companies NEA tags with at least one of these themes, e.g. AI, Infrastructure. Leave empty for every theme. ## `stages` (type: `array`): Keep only these stages, e.g. Seed, Early, Growth, Public/PIPES. Leave empty for every stage. ## `statuses` (type: `array`): Keep only these statuses as NEA publishes them, e.g. Private, Acquired, IPO/Acquired. Carried verbatim from NEA's page β€” this actor never decides that a company exited or failed. Leave empty for every status. ## `nameContains` (type: `string`): Free text kept only if it appears in the company name or NEA's own one-line description. ## `firstInvestedFrom` (type: `integer`): Earliest year of NEA's first investment, inclusive. Companies with no published year are excluded when this is set. ## `firstInvestedTo` (type: `integer`): Latest year of NEA's first investment, inclusive. Companies with no published year are excluded when this is set. ## `maxCompanies` (type: `integer`): The sweep reads this many companies from NEA's sitemap, in sitemap order, at 2 requests/second. NEA published 914 companies when this build was measured, so the default of 150 is a PARTIAL sweep and the report says so on its first line. Raise it toward 914 for a complete book β€” expect roughly one minute per 120 companies. ## Actor input object example ```json { "sectors": [ "Healthcare" ], "maxCompanies": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sectors": [ "Healthcare" ], "maxCompanies": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgenwatch/nea-portfolio-report").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "sectors": ["Healthcare"], "maxCompanies": 10, } # Run the Actor and wait for it to finish run = client.actor("nexgenwatch/nea-portfolio-report").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "sectors": [ "Healthcare" ], "maxCompanies": 10 }' | apify call nexgenwatch/nea-portfolio-report --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgenwatch/nea-portfolio-report" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/l2bqtLkRNaJdfQ9gy/builds/gVIyQnAvmBc1PYkrY/openapi.json