MCP Comparison
Compare features, tools, and capabilities of these MCP servers side by side.
PersonalizationMCP
PersonalizationMCP is a unified personal data hub built on MCP (Model Context Protocol) that enables AI assistants to access and reason over data from Steam, YouTube, Bilibili, Spotify, Reddit, and more. This repository showcases a Python-based MCP server that aggregates platform APIs, manages OAuth2 tokens, and exposes a rich set of tools to query user data, playlists, watch history, and social actions. It emphasizes local data handling, token management automation, and a modular architecture that makes it easy to add new platforms through the @mcp.tool() decorator and server integration. Ideal for developers building context-aware assistants who want a single, extensible backend to surface personal data across multiple services. The MCP server is designed to run locally on your machine with secure configuration, offering multiple installation paths (conda, uv, or pip with virtualenv). It includes a comprehensive set of available tools organized by platform, robust token management (notably YouTube), and practical guidance for configuration, testing, and cursor-based integration with consumer apps like Cursor. The project also provides detailed setup steps for each platform, including how to obtain API keys, cookies, and OAuth credentials, ensuring a smooth path from zero to a functioning personal data hub.
Hugging Face MCP Server
Hugging Face Official MCP Server connects your large language models (LLMs) to the Hugging Face Hub and thousands of Gradio AI Applications, enabling seamless MCP (Model Context Protocol) integration across multiple transports. It supports STDIO, SSE (to be deprecated but still commonly deployed), StreamableHTTP, and StreamableHTTPJson, with the Web Application allowing dynamic tool management and status updates. This MCP server is designed to be run locally or in Docker, and it provides integrations with Claude Desktop, Claude Code, Gemini CLI (and its extension), VSCode, and Cursor, making it easy to configure and manage MCP-enabled tools and endpoints. Tools such as hf_doc_search and hf_doc_fetch can be enabled to enhance document discovery, and an optional Authenticate tool can be included to handle OAuth challenges when called.
| Feature | PersonalizationMCP | Hugging Face MCP Server |
|---|---|---|
| Verified | ||
| Official | ||
| Tools Available | 75 | 3 |
| Has Installation Guide | ||
| Has Examples | ||
| Website | ||
| Source Code |
- get_steam_library()
- get_steam_recent_activity()
- get_steam_friends()
- get_steam_profile()
- get_player_achievements(app_id)
- get_user_game_stats(app_id)
- get_friends_current_games()
- compare_games_with_friend(friend_steamid)
- get_friend_game_recommendations(friend_steamid)
- search_youtube_videos(query)
- +65 more tools
- hf_doc_fetch
- hf_doc_search
- authenticate
Can't decide? Check out both MCP servers for more details.