MCP Comparison
Compare features, tools, and capabilities of these MCP servers side by side.
MarkItDown MCP
MarkItDown-MCP is a lightweight MCP (Model Context Protocol) server provided as the markitdown-mcp package. It exposes a STDIO, Streamable HTTP, and SSE MCP server designed for calling MarkItDown to convert content to Markdown. The package focuses on simplicity and accessibility, enabling you to run the MCP server locally via a simple CLI, or in Docker for containerized workflows, with integration options for Claude Desktop. The core capability is exposed through a single tool, convert_to_markdown(uri), which accepts a URI in http:, https:, file:, or data: schemes to fetch content and convert it to Markdown. This MCP server is easy to install with pip and can be used in various transport modes, including STDIO and HTTP/SSE, making it a flexible choice for automations and integrations.
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.
| Feature | MarkItDown MCP | PersonalizationMCP |
|---|---|---|
| Verified | ||
| Official | ||
| Tools Available | 2 | 75 |
| Has Installation Guide | ||
| Has Examples | ||
| Website | ||
| Source Code |
- convert_to_markdown(uri)
- mcpinspector
- 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
Can't decide? Check out both MCP servers for more details.