MCP Comparison
Compare features, tools, and capabilities of these MCP servers side by side.
ChainAware Behavioural Prediction MCP
The ChainAware Behavioural Prediction MCP is an MCP-based server that provides AI-powered tools to analyze wallet behaviour prediction, fraud detection, and rug pull prediction. Designed for Web3 security and DeFi analytics, it enables developers and platforms to integrate risk assessment, predictive wallet behavior insights, and rug-pull detection through MCP-compatible clients. The server exposes three specialized tools and uses Server-Sent Events (SSE) for real-time responses, helping safeguard DeFi users, monitor liquidity risks, and score wallet or contract trustworthiness. Access to production endpoints is API-key gated, reflecting a private backend architecture that supports secure, scalable risk analytics across wallets, contracts, and pools.
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 | ChainAware Behavioural Prediction MCP | PersonalizationMCP |
|---|---|---|
| Verified | ||
| Official | ||
| Tools Available | 3 | 75 |
| Has Installation Guide | ||
| Has Examples | ||
| Website | ||
| Source Code |
- predictive_fraud
- predictive_behaviour
- predictive_rug_pull
- 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.