Mathlas vs Discovery Engine

Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.

Compare
M
Mathlas
Archerkattri
🧮 Data Science Tools
D
Discovery Engine
leap-laboratories
🧮 Data Science Tools
SummaryAirtight math for agents: 3.7M-theorem search, PSLQ constant ID, OEIS, real Lean kernel checks, applicability checklists. No LLM inside, no API key.Superhuman exploratory data analysis that finds the feature interactions and subgroup effects that LLMs and manual exploration miss — with p-values, effect sizes, and literature citations. Data goes in, validated insights come out. Free for public data.
Quality signal23/100 (Emerging)23/100 (Emerging)
Install pathnpx · lownpx · low
Engagement 1 0 0 9 1 0 0
ToolsNot listed yetNot listed yet
Verified / officialNoNo
Open listingView MathlasView Discovery Engine
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