# EMEA Compliance MCP — AI Agent Outbound for Europe (`elisabethhitz/emea-compliance-mcp`) Actor EMEA sales compliance frameworks for AI agents. 7 EMEA countries. GDPR-compliant. By Elisabeth Hitz — 10+ years B2B enterprise sales experience. - **URL**: https://apify.com/elisabethhitz/emea-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 ## EMEA Compliance MCP — AI Agent Outbound for Europe **The only MCP server purpose-built for AI agents selling into Europe.** By [Elisabeth Hitz](https://www.elisabethhitz.com) — 10+ years B2B enterprise sales experience across ad-tech, media, finance, advertising, and SaaS. Five consecutive years overshooting quota across UK / Ireland / Spain / Germany / France / Netherlands / Norway. > **Disclaimer.** Reference frameworks for AI agent guidance. Not legal advice. Always validate compliance with qualified counsel before customer-facing deployment. --- ### What This Solves Your AI SDR works fine in the US. Then it tries to send a cold email to Berlin and gets blocked by GDPR. Or pitches to Paris ignoring CNIL opt-in rules. Or quotes UK contractors without flagging IR35. This MCP gives the AI agent structured EMEA compliance reasoning + sales nuance for 7 European markets. ### Tools (7) 1. `get_country_compliance_brief` — UK / IE / ES / DE / FR / NL / NO regulatory frame 2. `validate_outbound_message` — GDPR, ePrivacy, country-specific opt-in rules 3. `get_data_residency_requirements` — where can prospect data legally live 4. `get_country_sales_nuance` — formality, decision-cycle, gatekeepers, holiday calendars 5. `handle_emea_objection` — top 5 objections per country with localized responses 6. `recommend_localization_strategy` — translation depth, cultural adaptation, payment rails 7. `get_industry_regulatory_overlay` — fintech (MiFID), health (NHS), retail (PSD2), public-sector (DPA) ### Coverage - **United Kingdom** — UK GDPR, IR35, public-sector procurement - **Ireland** — DPC enforcement, English-language EMEA hub - **Spain** — LSSI, AEPD, regional dialect awareness - **Germany** — BDSG, works council, IT-Sicherheitsgesetz - **France** — CNIL strict opt-in, French-language requirements - **Netherlands** — Autoriteit Persoonsgegevens, English fluent enterprise - **Norway** — Datatilsynet, EEA but not EU, oil & gas vertical strong ### Use Cases - AI SDR platforms expanding from US-only → European outbound - Global B2B SaaS adding EU coverage to existing AI agents - In-house AI ops teams building proprietary multi-region sales agents - Enterprise SaaS RFPs requiring documented EMEA compliance posture ### 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. Five-year stretch overshooting quota in publicly-listed B2B SaaS. 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 EMEA Compliance tool to call ## `country` (type: `string`): EMEA market (required for most tools) ## `channel` (type: `string`): Channel for the template ## `company_stage` (type: `string`): Buyer org size ## `eor_objection` (type: `string`): Type of EOR/global hiring objection ## 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/emea-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/emea-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/emea-compliance-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=elisabethhitz/emea-compliance-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "EMEA Compliance MCP — AI Agent Outbound for Europe", "description": "EMEA sales compliance frameworks for AI agents. 7 EMEA countries. GDPR-compliant. By Elisabeth Hitz — 10+ years B2B enterprise sales experience.", "version": "0.0", "x-build-id": "knOU9JQB5DVdGnnii" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/elisabethhitz~emea-compliance-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-elisabethhitz-emea-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~emea-compliance-mcp/runs": { "post": { "operationId": "runs-sync-elisabethhitz-emea-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~emea-compliance-mcp/run-sync": { "post": { "operationId": "run-sync-elisabethhitz-emea-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_compliance_check", "get_stakeholder_map", "get_eor_objection_handler", "get_full_emea_pack" ], "type": "string", "description": "Which EMEA Compliance tool to call" }, "country": { "title": "Country", "enum": [ "uk", "ireland", "spain", "germany", "france", "netherlands", "nordics" ], "type": "string", "description": "EMEA market (required for most tools)" }, "channel": { "title": "Outreach Channel (for templates)", "enum": [ "cold_email", "linkedin_dm", "linkedin_inmail", "follow_up_day_3", "follow_up_day_7", "breakup" ], "type": "string", "description": "Channel for the template" }, "company_stage": { "title": "Company Stage (for stakeholder map)", "enum": [ "early_startup", "growth_stage", "mid_market", "enterprise" ], "type": "string", "description": "Buyer org size" }, "eor_objection": { "title": "EOR Objection Type", "enum": [ "use_contractors_instead", "not_ready_to_commit", "too_expensive", "we_already_have_entity", "compliance_unclear" ], "type": "string", "description": "Type of EOR/global hiring objection" } } }, "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 } } } } } } } } } } ```