YangLiangwei/PersonalizationMCP

Overview

A unified personal data hub built on the Model Context Protocol (MCP) that enables AI assistants to access user data from platforms like Steam, YouTube, and Bilibili. It aggregates personal digital life into a single MCP server, allowing assistants to retrieve context for personalized interactions. The tool is written in Python and is open source.

Best for

Best for
Developers building personalized AI assistants that need access to a user's digital footprint across multiple services

Use cases

• Connect an AI assistant to a user's Steam game library for personalized recommendations
• Provide an AI assistant with YouTube watch history to tailor content suggestions
• Expose Bilibili favorites and subscriptions to an AI for context-aware responses

Notes

A unified personal data hub built on the Model Context Protocol (MCP) that enables AI assistants to access user data from platforms like Steam, YouTube, and Bilibili. It aggregates personal digital life into a single MCP server, allowing assistants to retrieve context for personalized interactions. The tool is written in Python and is open source.

54 stars on GitHub. Last updated 2026-03-24. Licensed MIT.

Use cases

• Connect an AI assistant to a user’s Steam game library for personalized recommendations
• Provide an AI assistant with YouTube watch history to tailor content suggestions
• Expose Bilibili favorites and subscriptions to an AI for context-aware responses

Pros

• Unifies multiple platform data sources into one MCP server for easy integration
• Open source with a clear focus on personalization and user control
• Leverages the MCP standard, making it compatible with many AI assistants

Cons

• Relies on third-party platform APIs which may change or require authentication
• Limited to the platforms currently supported (Steam, YouTube, Bilibili, etc.)
• Requires manual setup and configuration to connect each user’s accounts

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.