# LATAM Startup & VC Funding Directory Scraper (`jungle_synthesizer/latam-vc-startup-directory-scraper`) Actor Scrape LATAM startup funding rounds from LatamList and Contxto. Extracts company name, country, sector, stage, amount, lead investor, and participants from funding articles. Covers Brazil, Mexico, Colombia, Argentina, Chile, and more. Ideal for VCs and founders tracking LATAM deal flow. - **URL**: https://apify.com/jungle\_synthesizer/latam-vc-startup-directory-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Lead generation, Business, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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.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 ## LATAM Startup and VC Funding Directory Scraper Scrape LATAM startup funding rounds from [LatamList](https://latamlist.com) and [Contxto](https://contxto.com). Extracts company name, country, sector, round stage, amount in USD, lead investor, and participating investors from funding articles across Brazil, Mexico, Colombia, Argentina, Chile, and the rest of Latin America. --- ### LATAM Funding Scraper Features - Pulls funding rounds from two complementary LATAM news sources — LatamList and Contxto — in one run - Returns funding amount in both human-readable form (`$5M`) and parsed number (`5.0` for $5M, `1200.0` for $1.2B) - Captures lead investor and participating investors as separate fields - Sector and round stage parsed out of article body — Fintech, HealthTech, AI, Logistics, Seed, Series A, B, C - Filter by country to pull deal flow for a single market - No proxy required — both sources are publicly accessible --- ### Who Uses LATAM Funding Data? - **VCs and angel investors** — Track LATAM deal flow in near-real time without subscribing to a regional research service - **Founders** — Map which investors are writing checks in your sector and stage before you start fundraising - **Corporate dev and M&A teams** — Monitor emerging targets in specific verticals across Latin America - **Researchers and journalists** — Build longitudinal datasets on capital flows into LATAM by country and sector - **Sales teams at infra and SaaS vendors** — Find newly funded startups that just took on burn rate they need to spend somewhere --- ### How the LATAM Funding Scraper Works 1. **Pick a source** — `all` for LatamList + Contxto, or either site solo. 2. **Article crawl** — The scraper walks each source's funding feed, deduplicates by URL, and pulls each article body. 3. **Structured parsing** — Company name, country, sector, round stage, amount, and investors are extracted from the article with site-specific selectors and pattern matching. 4. **Export** — One record per funding round in your Apify dataset. --- ### Input #### All sources, all countries ```json { "source": "all", "country": "", "maxItems": 200 } ```` #### Single country ```json { "source": "all", "country": "Brazil", "maxItems": 100 } ``` #### LatamList only ```json { "source": "latamlist", "maxItems": 50 } ``` | Field | Type | Default | Description | |-------|------|---------|-------------| | source | string | `all` | `all`, `latamlist`, or `contxto`. | | country | string | — | LATAM country name (e.g. `Brazil`, `Mexico`). Empty = all countries. | | maxItems | integer | 10 | Cap on funding rounds returned. | *** ### LATAM Funding Scraper Output Fields ```json { "company_name": "Kavak", "source_url": "https://latamlist.com/kavak-raises-700m-series-e", "source_site": "latamlist", "announced_date": "2026-04-18", "country": "Mexico", "sector": "Mobility", "round_stage": "Series E", "amount_usd": "$700M", "amount_usd_number": 700.0, "lead_investor": "General Atlantic", "participating_investors": "SoftBank, Tiger Global, Greenoaks", "description": "Kavak is a Mexico City-based marketplace for buying and selling used cars across LATAM.", "article_title": "Kavak raises $700M Series E to expand across LATAM", "scraped_at": "2026-05-11T04:22:55.842Z" } ``` | Field | Type | Description | |-------|------|-------------| | company\_name | string | Startup or company name | | source\_url | string | URL of the original article | | source\_site | string | Publication that reported the round (`latamlist` or `contxto`) | | announced\_date | string | Round announcement date (YYYY-MM-DD) | | country | string | Country where the startup is headquartered | | sector | string | Industry or sector (Fintech, HealthTech, AI, Logistics, etc.) | | round\_stage | string | Funding stage (Seed, Series A, B, C, etc.) | | amount\_usd | string | Funding amount as published (e.g. `$5M`, `$1.2B`) | | amount\_usd\_number | number | Parsed amount in millions USD (e.g. `5.0` for $5M) | | lead\_investor | string | Lead investor name(s) | | participating\_investors | string | Comma-separated participating investors | | description | string | Brief description of the startup from the article | | article\_title | string | Original article headline | | scraped\_at | string | ISO timestamp when the record was scraped | *** ### FAQ #### How do I track LATAM startup funding without a research subscription? LATAM Funding Scraper pulls from LatamList and Contxto, the two most active English-language LATAM funding desks. Set the source to `all`, optionally filter by country, and run. New rounds land in your dataset as soon as they're posted. #### How much does this actor cost to run? LATAM Funding Scraper uses pay-per-event pricing on the `default_2603_basic` profile at a 1.0x coefficient. No proxy fees. A 200-round monthly digest costs cents in platform fees. #### Can I filter by sector or round size? LATAM Funding Scraper exposes country and source filters at input. Sector and round size are returned as structured fields (`sector`, `amount_usd_number`), so a one-line downstream filter slices the dataset by Fintech, Series A+, or any combination. #### What countries does this cover? LATAM Funding Scraper covers everything LatamList and Contxto report on — primarily Brazil, Mexico, Colombia, Argentina, Chile, Peru, Uruguay, and Costa Rica. Use the `country` filter to narrow to one market. #### Does this actor need proxies? LATAM Funding Scraper runs proxy-free. Both source sites serve traffic publicly and don't rate-limit at the volumes this actor produces. *** ### Need More Features? Need Crunchbase or PitchBook enrichment, valuation parsing, or a webhook on every new round? [Open an issue](https://console.apify.com/actors/issues) or get in touch. ### Why Use LATAM Funding Scraper? - **Two sources, one schema** — LatamList and Contxto often cover different deals. Running both and deduplicating by URL gets you broader coverage than either alone. - **Amount in both shapes** — `amount_usd` as the published string and `amount_usd_number` as parsed millions. Pick the one you need downstream — most pipelines want the number. - **Lead vs participating split** — Lead investor is separate from the rest, which matters when you're tracking who's actually setting valuations in the region. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `source` (type: `string`): Which news source(s) to scrape. 'latamlist' for LatamList.com only, 'contxto' for Contxto.com only, or 'all' for both. ## `country` (type: `string`): Filter by LATAM country. Leave empty for all countries. Examples: 'Brazil', 'Mexico', 'Colombia', 'Argentina', 'Chile'. ## `maxItems` (type: `integer`): Maximum number of funding records to return. Default is 10 for quick previews. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "source": "all", "country": "", "maxItems": 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "source": "all", "country": "", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/latam-vc-startup-directory-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "source": "all", "country": "", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/latam-vc-startup-directory-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "source": "all", "country": "", "maxItems": 10 }' | apify call jungle_synthesizer/latam-vc-startup-directory-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/latam-vc-startup-directory-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LATAM Startup & VC Funding Directory Scraper", "description": "Scrape LATAM startup funding rounds from LatamList and Contxto. Extracts company name, country, sector, stage, amount, lead investor, and participants from funding articles. Covers Brazil, Mexico, Colombia, Argentina, Chile, and more. Ideal for VCs and founders tracking LATAM deal flow.", "version": "0.1", "x-build-id": "2oiQrj95mje35iI7N" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~latam-vc-startup-directory-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-latam-vc-startup-directory-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~latam-vc-startup-directory-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-latam-vc-startup-directory-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~latam-vc-startup-directory-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-latam-vc-startup-directory-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "sp_intended_usage", "sp_improvement_suggestions" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "source": { "title": "Data Source", "enum": [ "all", "latamlist", "contxto" ], "type": "string", "description": "Which news source(s) to scrape. 'latamlist' for LatamList.com only, 'contxto' for Contxto.com only, or 'all' for both.", "default": "all" }, "country": { "title": "Country Filter", "type": "string", "description": "Filter by LATAM country. Leave empty for all countries. Examples: 'Brazil', 'Mexico', 'Colombia', 'Argentina', 'Chile'.", "default": "" }, "maxItems": { "title": "Max Items", "minimum": 1, "type": "integer", "description": "Maximum number of funding records to return. Default is 10 for quick previews.", "default": 10 } } }, "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 } } } } } } } } } } ```