# Gbif Scraper (`openclawmara/gbif-scraper`) Actor - **URL**: https://apify.com/openclawmara/gbif-scraper.md - **Developed by:** [OpenClaw Mara](https://apify.com/openclawmara) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 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 ## GBIF Biodiversity & Species Scraper Search and extract species data and occurrence records from [GBIF](https://gbif.org) — the world's largest biodiversity database with 2.4B+ occurrence records. **No API key needed.** ### Features - 🌿 **2.4B+ occurrence records** from 80,000+ datasets worldwide - 🔍 **Species search** — by scientific name, common name, or keyword - 📍 **Geographic occurrences** — lat/long, country, locality, collection date - 🏷️ **Full taxonomy** — kingdom through species, IUCN status - 🌍 **Country filter** — focus on specific regions - 📊 **Collection metadata** — institution, collector, dataset source - ⚡ **Official API** — no authentication, no blocking ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `speciesQueries` | string[] | `[]` | Search by species name | | `maxSpecies` | number | `20` | Max species per query | | `includeOccurrences` | boolean | `false` | Fetch observation records | | `maxOccurrences` | number | `50` | Max occurrences per species | | `country` | string | `""` | ISO country filter (US, BR, etc.) | | `hasCoordinate` | boolean | `true` | Only georeferenced records | ### Example ```json { "speciesQueries": ["Ailuropoda melanoleuca"], "includeOccurrences": true, "maxOccurrences": 20, "country": "CN" } ```` ### Output ```json { "type": "species", "scientificName": "Ailuropoda melanoleuca (David, 1869)", "canonicalName": "Ailuropoda melanoleuca", "kingdom": "Animalia", "family": "Ursidae", "iucnRedListCategory": "VU", "occurrences": [ { "decimalLatitude": 30.7, "decimalLongitude": 103.0, "country": "China", "year": 2023, "basisOfRecord": "HUMAN_OBSERVATION" } ] } ``` ### Use Cases - **Conservation research** — track endangered species distributions - **Ecological modeling** — species distribution models with real occurrence data - **Environmental assessment** — biodiversity surveys for specific regions - **Education** — explore taxonomy and geographic distributions - **Citizen science** — aggregate observation data # Actor input Schema ## `speciesQueries` (type: `array`): Search species by name (e.g. 'Ailuropoda melanoleuca', 'giant panda', 'orchid') ## `maxSpecies` (type: `integer`): Maximum species to return per search query ## `includeOccurrences` (type: `boolean`): Fetch geographic occurrence records for each species (where observed/collected) ## `maxOccurrences` (type: `integer`): Maximum occurrence records per species ## `country` (type: `string`): Filter occurrences by country (ISO 2-letter code, e.g. 'US', 'BR', 'AU'). Leave empty for global. ## `hasCoordinate` (type: `boolean`): Only include occurrences with GPS coordinates ## Actor input object example ```json { "maxSpecies": 20, "includeOccurrences": false, "maxOccurrences": 50, "hasCoordinate": true } ``` # 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("openclawmara/gbif-scraper").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/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("openclawmara/gbif-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call openclawmara/gbif-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=openclawmara/gbif-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gbif Scraper", "version": "1.0", "x-build-id": "qhCpNicSBSm3dxgrt" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/openclawmara~gbif-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-openclawmara-gbif-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/openclawmara~gbif-scraper/runs": { "post": { "operationId": "runs-sync-openclawmara-gbif-scraper", "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/openclawmara~gbif-scraper/run-sync": { "post": { "operationId": "run-sync-openclawmara-gbif-scraper", "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": { "speciesQueries": { "title": "Species Search Queries", "type": "array", "description": "Search species by name (e.g. 'Ailuropoda melanoleuca', 'giant panda', 'orchid')", "items": { "type": "string" } }, "maxSpecies": { "title": "Max Species per Query", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum species to return per search query", "default": 20 }, "includeOccurrences": { "title": "Include Occurrence Records", "type": "boolean", "description": "Fetch geographic occurrence records for each species (where observed/collected)", "default": false }, "maxOccurrences": { "title": "Max Occurrences per Species", "minimum": 1, "maximum": 300, "type": "integer", "description": "Maximum occurrence records per species", "default": 50 }, "country": { "title": "Country Filter", "type": "string", "description": "Filter occurrences by country (ISO 2-letter code, e.g. 'US', 'BR', 'AU'). Leave empty for global." }, "hasCoordinate": { "title": "Only Georeferenced", "type": "boolean", "description": "Only include occurrences with GPS coordinates", "default": true } } }, "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 } } } } } } } } } } ```