# LATAM Compliance MCP — AI Agent Outbound for Latin America (`elisabethhitz/latam-compliance-mcp`) Actor MCP for AI agents selling into Latin America. 7 tools: country briefs (Mexico/Brazil/Colombia/Argentina/Chile/Peru), Spanish + Portuguese templates, etiquette guides, follow-up cadences, LGPD/LFPDPPP compliance. By Elisabeth Hitz. - **URL**: https://apify.com/elisabethhitz/latam-compliance-mcp.md - **Developed by:** [Elisabeth](https://apify.com/elisabethhitz) (community) - **Categories:** AI, Agents - **Stats:** 0 total users, 0 monthly users, 0.0% 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 ## LATAM Compliance MCP — AI Agent Outbound for Latin America **Country briefs and compliance reasoning for AI agents selling into Mexico, Brazil, Colombia, Argentina, Chile, Peru, and Costa Rica.** By [Elisabeth Hitz](https://www.elisabethhitz.com) — 10+ years B2B enterprise sales experience. Spanish + Portuguese fluent. > **Disclaimer.** Reference frameworks for AI agent guidance. Not legal advice. Validate with qualified counsel before customer deployment. --- ### What This Solves AI SDR platforms working in US English break in LATAM: LGPD (Brazil), LFPDPPP (Mexico), CFDI invoicing, Colombian Habeas Data, Argentine PDPA, business culture (relationship-first vs task-first), language depth requirements (Spanish vs Portuguese vs regional dialects), payment rails (PIX, OXXO, SPEI). This MCP gives AI agents structured LATAM context. ### Tools (7) 1. `get_country_brief` — Mexico / Brazil / Colombia / Argentina / Chile / Peru / Costa Rica 2. `validate_latam_outbound_message` — LGPD / LFPDPPP / Habeas Data compliance 3. `get_invoicing_requirements` — CFDI (Mexico), NFe (Brazil), local invoice rules 4. `get_business_culture_brief` — relationship-building, decision-cycle, family-business dynamic 5. `handle_latam_objection` — top 5 objections per country with cultural nuance 6. `recommend_payment_rail` — PIX, OXXO, SPEI, regional credit-card networks 7. `get_industry_regulatory_overlay` — finance, fintech, healthcare, telecom, public-sector ### Coverage (7 countries) Mexico, Brazil, Colombia, Argentina, Chile, Peru, Costa Rica. ### Use Cases - AI SDR platforms launching in LATAM - B2B SaaS adding Spanish + Portuguese coverage - Fintech AI agents handling Latin American invoicing - Customer-success AI managing LATAM accounts ### Pricing Pay-per-event. Compute units billed per Apify standard. ### Integration MCP-compatible: Claude Desktop, Cursor, Cline, Continue, VS Code Copilot Agent, custom MCP clients. ### License MIT. ### Author Elisabeth Hitz — Swiss-American B2B sales executive based in Barcelona. 10+ years closing enterprise deals across ad-tech, SaaS, media, finance, and global hiring. 5 languages fluent (English, Spanish, Portuguese, French, German). Building MCP infrastructure for AI sales agents. - [elisabethhitz.com](https://www.elisabethhitz.com) - [LinkedIn](https://www.linkedin.com/in/elisabethhitz) # Actor input Schema ## `tool` (type: `string`): Which LATAM tool to call ## `country` (type: `string`): Country in Latin America ## `channel` (type: `string`): Channel for the template ## `company_stage` (type: `string`): Buyer org size ## Actor input object example ```json {} ```` # 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("elisabethhitz/latam-compliance-mcp").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("elisabethhitz/latam-compliance-mcp").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 elisabethhitz/latam-compliance-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=elisabethhitz/latam-compliance-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LATAM Compliance MCP — AI Agent Outbound for Latin America", "description": "MCP for AI agents selling into Latin America. 7 tools: country briefs (Mexico/Brazil/Colombia/Argentina/Chile/Peru), Spanish + Portuguese templates, etiquette guides, follow-up cadences, LGPD/LFPDPPP compliance. By Elisabeth Hitz.", "version": "0.0", "x-build-id": "7x5JWnzjHsyQD7qOi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/elisabethhitz~latam-compliance-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-elisabethhitz-latam-compliance-mcp", "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/elisabethhitz~latam-compliance-mcp/runs": { "post": { "operationId": "runs-sync-elisabethhitz-latam-compliance-mcp", "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/elisabethhitz~latam-compliance-mcp/run-sync": { "post": { "operationId": "run-sync-elisabethhitz-latam-compliance-mcp", "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": [ "tool" ], "properties": { "tool": { "title": "Tool", "enum": [ "get_country_brief", "get_outreach_template", "get_followup_cadence", "get_etiquette_guide", "get_stakeholder_map", "get_compliance_check", "get_full_latam_pack" ], "type": "string", "description": "Which LATAM tool to call" }, "country": { "title": "LATAM Country", "enum": [ "mexico", "brazil", "colombia", "argentina", "chile", "peru" ], "type": "string", "description": "Country in Latin America" }, "channel": { "title": "Outreach Channel", "enum": [ "cold_email", "linkedin_dm", "whatsapp", "follow_up_day_3", "follow_up_day_7" ], "type": "string", "description": "Channel for the template" }, "company_stage": { "title": "Company Stage", "enum": [ "early_startup", "growth_stage", "mid_market", "enterprise" ], "type": "string", "description": "Buyer org size" } } }, "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 } } } } } } } } } } ```