
The core idea is simple: instead of training a theorem-proving-specific pipeline from scratch, we explore whether a general coding agent can be turned into a strong formal mathematics reasoner by giving it the right tools through MCP.
Numina-Lean-Agent integrates Lean interaction, semantic theorem retrieval, informal proving, and multi-model discussion. In our experiments, it solves 12/12 Putnam 2025 problems, matching or surpassing several closed-source systems, while remaining #opensource.
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