# NOAA Essential Fish Habitat Screener — EFH Consultation Check (`malonestar/noaa-efh-consultation-screener`) Actor Screen coastal & offshore coordinates against live NOAA Essential Fish Habitat (EFH) polygons. Per point: designated species/sites, life stages, fishery-management council, acres, state-waters flag, and a Magnuson-Stevens EFH consultation flag. Batch, MCP-ready. $0.01 per asset check. - **URL**: https://apify.com/malonestar/noaa-efh-consultation-screener.md - **Developed by:** [Kyle Maloney](https://apify.com/malonestar) (community) - **Categories:** Agents, Developer tools, Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## NOAA Essential Fish Habitat Screener — EFH Consultation Check Screen any set of coastal or offshore coordinates against **live NOAA Essential Fish Habitat (EFH)** polygons with a single spatial query per point. Get a grounded yes/no — is the point inside designated EFH, which **species/sites** and **life stages** overlap it, the **fishery-management council** that manages them, the habitat **acres**, a **state-waters** flag, and a **`nmfs_efh_consultation_likely`** flag — with a source citation on every row. Any federal action (permit, funding, or authorization) that may adversely affect EFH triggers **Magnuson-Stevens Act Section 305(b)(2) consultation** with NOAA Fisheries. This actor is the marine sibling of the **FWS Critical Habitat Screener** (ESA Section 7) and pairs naturally with the **BOEM Offshore Wind Lease Tracker** for offshore siting due diligence. Data source: NOAA Essential Fish Habitat national inventory ArcGIS FeatureServer (`services2.arcgis.com/FiaPA4ga0iQKduv3/.../nationwide_efh_1`), queried live via a server-side point-intersect (`returnGeometry=false`, so the large council-scale polygons are never downloaded). No scraping, no API key required. ### Who it's for - **Offshore wind & marine energy siting teams** screening lease areas, cable routes, and export corridors for EFH before survey and permitting. - **Ports, dredging & marine construction** de-risking a project footprint — an EFH hit can add an EFH assessment and NOAA Fisheries consultation to the schedule. - **Aquaculture developers** siting net-pens/leases relative to designated habitat and HAPCs. - **Environmental consultants & NEPA/marine-permitting teams** doing early desktop screening before an EFH Assessment or Biological Evaluation. - **AI agents / MCP tool chains** running automated marine site diligence as one step in a larger permitting or acquisition workflow. ### Example input ```json { "assets": [ { "lat": 28.5, "lon": -91.0, "label": "Gulf of Mexico (offshore Louisiana)" }, { "lat": 41.6, "lon": -70.7, "label": "Nantucket Sound cable landing" }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver CO (inland control)" } ], "radiusMiles": 0, "maxAssets": 500 } ```` #### Verified sample run A real 6-site run (2026-07-21, `radiusMiles: 0`) returned **152 rows** and 0 errors. Coastal and offshore points return one row per EFH designation, so the row count per site reflects how many overlapping species/lifestage/council designations apply there: | Asset | Rows | Consultation flag | |---|---|---| | Gulf of Mexico (offshore Louisiana) | 13 | true | | Galveston, TX (nearshore) | 17 | true | | Chesapeake Bay mouth, VA | 37 | true | | Massachusetts Bay | 76 | true | | San Pedro Bay, CA | 8 | true | | Denver, CO (inland control) | 1 (CLEAR) | false | The Gulf point's 13 rows span the Gulf of Mexico Fishery Management Council plus Atlantic Highly Migratory Species designations. The inland control returned a single valid CLEAR row (`in_efh: false`) — a billable result, not an error. This exact run is published as the actor's example task, so you can open it and re-run it as-is. ### Output fields (one row per EFH species/lifestage hit; one CLEAR row when clear) | Field | Description | |---|---| | `asset_label` | Your name for the screened point, echoed back | | `asset_lat` / `asset_lon` | Coordinates screened | | `radius_miles` | Buffer radius used (0 = pure point-in-polygon) | | `in_efh` | true / false / null (null = ERROR row) | | `efh_site_name` | Species or EFH site whose habitat this point intersects | | `life_stage` | Life stage designated (ALL, Eggs, Larval, Juvenile, Adult, ...) | | `designation_type` | `EFH` or `HAPC` (Habitat Area of Particular Concern) | | `is_hapc` | true when the designation is a HAPC | | `fmc_code` / `fmc_name` | Managing fishery-management council (code + full name) | | `region` | NOAA administrative region code | | `acres` | Area of the intersecting EFH polygon in acres | | `in_state_waters` | true/false/null — in state waters (~3 nm) vs federal | | `centroid_lat` / `centroid_lon` | Centroid of the intersecting polygon | | `council_text_url` | Link to the council's EFH text description (PDF) | | `nmfs_efh_consultation_likely` | true when the point intersects any EFH | | `checked_at` | UTC timestamp of the check | | `error` | Populated only on invalid-input / service-error rows | | `disclaimer` / `source_url` | Advisory notice + exact FeatureServer queried | ### Use as an MCP tool This actor is discoverable and callable by AI agents (Claude, Cursor, etc.) via [mcp.apify.com](https://mcp.apify.com). Pass an array of `{lat, lon, label}` points and get back a grounded, cited in/near-EFH verdict per point — clean input/output for chaining into larger marine site-diligence or permitting agent workflows. ### FAQ **Does this actor need an API key?** No — the NOAA EFH ArcGIS service is public and keyless. **Inland points return nothing — is that a bug?** No. EFH is a **coastal and marine** designation only. An inland point (or any point with no EFH nearby) legitimately returns a single CLEAR row with `in_efh = false` — a valid, billable result, not an error. **Does an EFH hit mean I definitely need to consult?** No. `nmfs_efh_consultation_likely` flags that your point intersects designated EFH, which is the trigger *condition* for Magnuson-Stevens Section 305(b)(2) consultation **when a federal action may adversely affect that habitat**. Whether consultation is actually required is determined by the federal action agency and NOAA Fisheries. Confirm with the regional NOAA Fisheries Habitat Conservation Division ([habitat.noaa.gov](https://www.habitat.noaa.gov)). **What's the difference between EFH and HAPC?** EFH is the broad designation of waters and substrate necessary to fish for spawning, breeding, feeding, or growth. A **HAPC** (Habitat Area of Particular Concern) is a subset of EFH singled out for ecological importance, sensitivity, or rarity — it warrants extra scrutiny in consultation. **Why can one point return many rows?** EFH designations overlap heavily — a single Gulf point can fall inside Red Drum, Reef Fish, Shrimp, Coastal Migratory Pelagics, and several Highly Migratory Species (shark/tuna) habitats at once. The actor returns every distinct species/lifestage/council overlap, deduped. **How is pricing calculated?** $10 per 1,000 result rows ($0.01/row) — one row per EFH species hit, or one row per clear point. No charge for actor start. **Can I screen a large portfolio?** Yes — pass up to 2,000 points per run via `maxAssets`; each point queries the live ArcGIS service in sequence. ### Related screeners This actor is part of a family of single-coordinate federal due-diligence screeners that all take the same `assets[]{lat,lon,label}` input shape, so you can run several over the same site list and join the results per site. - [Site Due Diligence Bundle](https://apify.com/malonestar/site-due-diligence-bundle) — 15 federal overlays for one coordinate in a single call. - [BOEM Offshore Wind Lease Tracker](https://apify.com/malonestar/boem-offshore-wind-lease-tracker) — BOEM offshore wind lease areas and planning areas. - [FWS Critical Habitat Screener](https://apify.com/malonestar/fws-critical-habitat-screener) — the terrestrial sibling: ESA Section 7 designated critical habitat. - [EPA Impaired Waters 303(d) Screener](https://apify.com/malonestar/epa-impaired-waters-303d-screener) — Clean Water Act 303(d) impaired waters near the site. - [Wild & Scenic River Proximity Screener](https://apify.com/malonestar/wild-scenic-river-proximity-screener) — designated Wild & Scenic River corridors and Section 7 exposure. # Actor input Schema ## `assets` (type: `array`): List of coastal/offshore points to screen against live NOAA Essential Fish Habitat (EFH) polygons. Each item is an object: {"lat": \, "lon": \, "label": ""}. Each EFH species/lifestage overlap produces one billable dataset row; a point with no EFH (e.g. an inland point — EFH is coastal/marine only) produces one billable CLEAR row. Invalid points produce an ERROR row and the run continues. ## `radiusMiles` (type: `number`): Optional buffer, in statute miles, added around each point. Default 0 = pure point-in-polygon (is the point inside designated EFH?). Set > 0 to also catch EFH near — but not directly under — the point (useful for a site adjacent to a habitat boundary). Clamped to 0..25. ## `maxAssets` (type: `integer`): Safety cap on the number of assets screened per run. Assets beyond this cap are skipped with a warning. ## Actor input object example ```json { "assets": [ { "lat": 28.5, "lon": -91, "label": "Gulf of Mexico (offshore Louisiana)" }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver CO (inland control — no EFH)" } ], "radiusMiles": 0, "maxAssets": 500 } ``` # Actor output Schema ## `results` (type: `string`): The default dataset with one EFH row per asset check. # 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 = { "assets": [ { "lat": 28.5, "lon": -91, "label": "Gulf of Mexico (offshore Louisiana)" }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver CO (inland control — no EFH)" } ], "radiusMiles": 0, "maxAssets": 500 }; // Run the Actor and wait for it to finish const run = await client.actor("malonestar/noaa-efh-consultation-screener").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 = { "assets": [ { "lat": 28.5, "lon": -91, "label": "Gulf of Mexico (offshore Louisiana)", }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver CO (inland control — no EFH)", }, ], "radiusMiles": 0, "maxAssets": 500, } # Run the Actor and wait for it to finish run = client.actor("malonestar/noaa-efh-consultation-screener").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 '{ "assets": [ { "lat": 28.5, "lon": -91, "label": "Gulf of Mexico (offshore Louisiana)" }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver CO (inland control — no EFH)" } ], "radiusMiles": 0, "maxAssets": 500 }' | apify call malonestar/noaa-efh-consultation-screener --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=malonestar/noaa-efh-consultation-screener", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "NOAA Essential Fish Habitat Screener — EFH Consultation Check", "description": "Screen coastal & offshore coordinates against live NOAA Essential Fish Habitat (EFH) polygons. Per point: designated species/sites, life stages, fishery-management council, acres, state-waters flag, and a Magnuson-Stevens EFH consultation flag. Batch, MCP-ready. $0.01 per asset check.", "version": "1.0", "x-build-id": "K82JYpnef6vvW3Y3g" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/malonestar~noaa-efh-consultation-screener/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-malonestar-noaa-efh-consultation-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/malonestar~noaa-efh-consultation-screener/runs": { "post": { "operationId": "runs-sync-malonestar-noaa-efh-consultation-screener", "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/malonestar~noaa-efh-consultation-screener/run-sync": { "post": { "operationId": "run-sync-malonestar-noaa-efh-consultation-screener", "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": { "assets": { "title": "Assets (coordinates to screen)", "type": "array", "description": "List of coastal/offshore points to screen against live NOAA Essential Fish Habitat (EFH) polygons. Each item is an object: {\"lat\": , \"lon\": , \"label\": \"\"}. Each EFH species/lifestage overlap produces one billable dataset row; a point with no EFH (e.g. an inland point — EFH is coastal/marine only) produces one billable CLEAR row. Invalid points produce an ERROR row and the run continues." }, "radiusMiles": { "title": "Search radius (miles)", "minimum": 0, "maximum": 25, "type": "number", "description": "Optional buffer, in statute miles, added around each point. Default 0 = pure point-in-polygon (is the point inside designated EFH?). Set > 0 to also catch EFH near — but not directly under — the point (useful for a site adjacent to a habitat boundary). Clamped to 0..25.", "default": 0 }, "maxAssets": { "title": "Max asset checks", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Safety cap on the number of assets screened per run. Assets beyond this cap are skipped with a warning.", "default": 500 } } }, "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 } } } } } } } } } } ```