Dataprivacy Ai Mcp
Let your coding agent classify personal data, check lawful bases, and draft GDPR-style privacy artifacts without leaving the chat.
Overview
Dataprivacy-ai-mcp is a MCP server for the Ship phase that lets agents classify personal data, assess lawful basis, and generate privacy documentation through stdio tool calls.
What is this MCP server?
- MCP tools to classify fields and datasets as personal data via stdio transport (PyPI package dataprivacy-ai-mcp v1.0.8)
- Assess lawful basis for processing aligned to common GDPR decision patterns
- Generate privacy documentation snippets agents can fold into policies or technical specs
- Stdio MCP server for Claude Code, Cursor, and other MCP-capable agents
- CSOAI-ORG maintained automation server on the official MCP schema
- Server version 1.0.8 on MCP schema 2025-12-11
- PyPI package identifier dataprivacy-ai-mcp with stdio transport
- Advertised tool themes: classify personal data, assess lawful basis, generate privacy deliverables
What problem does it solve?
Solo builders struggle to map what they collect to GDPR concepts and lawful bases while still iterating in the IDE.
Who is it for?
Indie SaaS founders doing a compliance pass before launch or before adding analytics and auth flows.
Skip if: Teams that already run enterprise privacy management software or need certified legal sign-off only.
What do I get? / Deliverables
After install, your agent can invoke privacy classification and basis-assessment tools and drop generated privacy text into your specs or policies.
- Personal-data classification results for described datasets or fields
- Lawful-basis assessment summaries agents can cite in specs
- Generated privacy documentation fragments for policies or DPIA drafts
Recommended MCP Servers
Journey fit
How it compares
MCP compliance assistant for agents, not a hosted privacy vault or DPA management SaaS.
Common Questions / FAQ
Who is dataprivacy-ai-mcp for?
Solo and indie builders using Claude Code or Cursor who need agent-callable privacy classification and documentation helpers during ship and security review.
When should I use dataprivacy-ai-mcp?
Use it when you are defining data flows, updating a privacy policy draft, or checking lawful basis before you enable new features that touch user data.
How do I add dataprivacy-ai-mcp to my agent?
Install the PyPI package dataprivacy-ai-mcp, add a stdio MCP server entry pointing at that package, restart your agent, and confirm the classify and assess tools appear in the tool list.