Numina-Lean-Agent: An Open and General Agentic Reasoning System for Formal Mathematics
Paper · 2026 · Junqi Liu, Zihao Zhou, Zekai Zhu et al.
Summary
Recent agentic systems for formal theorem proving perform well, but they often depend on custom pipelines and specially trained provers, and many are closed-source. The authors propose a different approach: use an off-the-shelf coding agent as the reasoner. Their system, Numina-Lean-Agent, pairs Claude Code with Numina-Lean-MCP, a set of tools exposed through the Model Context Protocol. These tools let the agent compile and inspect Lean code, search for relevant theorems, obtain informal proofs, and consult other LLMs. The agent decides on its own which tool to call. Because no model is trained, a stronger base model can simply be swapped in.
With Claude Opus 4.5 as the base model, the system solved every Putnam 2025 problem. This ties AxiomProver and beats Harmonic's Aristotle. It also helped a mathematician and a Lean expert formalize a recent result on Brascamp–Lieb inequalities, showing it is useful beyond benchmarks. The code and all solutions are publicly released, which supports reproducible research in formal mathematics.
Key points
- Toolkit. Numina-Lean-MCP bundles four components:
- Lean-LSP-MCP, for goal queries, diagnostics, running code and multi-attempt tactic trials;
- LeanDex, a new agentic semantic search over mathlib and FLT for Lean v4.26.0, built on LeanExplore;
- an Informal Prover, a generator–verifier loop on Gemini-3-Pro-Preview with up to 20 rounds, where a proof must pass three independent checks;
- a Discussion Partner that queries external LLMs.
- Putnam 2025 result: 12/12. The evaluation used Seed-Prover 1.5's formal statements, strictly sequential execution and no web access. The budget was about $50 per problem, raised to roughly $1000 for A5.
- Concise proofs. For some problems, such as B1, the system's proofs were shorter than those of AxiomProver and Seed-Prover 1.5.
- Brascamp–Lieb formalization. In under two weeks, the team produced more than 8,000 lines of Lean. The agent contributed about 70 new definitions and lemmas, and it detected and fixed false statements on its own.
- Limitations.
- Generated proofs tend to be verbose and not idiomatic Mathlib style.
- The agent struggles with type-level issues; for example, a Real to NNReal conversion blocked one proof.
Institutions
Fields, topics and concepts
📚 Shelves 3The field of science this work belongs to (OpenAlex fields).Computer Science · 19,503 worksArtificial Intelligence · 18,805 worksComputational Theory and Mathematics · 496 works
🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1,948 works
Cite
Cite as Junqi Liu, Zihao Zhou, Zekai Zhu, Marco Dos Santos, Weikun He, Jiawei Liu, Ran Wang, Yunzhou Xie, Junqiao Zhao, Qiufeng Wang, Lihong Zhi, Jia Li and Wenda Li. 2026. Numina-Lean-Agent: An Open and General Agentic Reasoning System for Formal Mathematics. arXiv:2601.14027.
@misc{liu2026numina,
title = {{Numina-Lean-Agent: An Open and General Agentic Reasoning System for Formal Mathematics}},
author = {Junqi Liu, Zihao Zhou, Zekai Zhu, Marco {Dos Santos}, Weikun He, Jiawei Liu, Ran Wang, Yunzhou Xie, Junqiao Zhao, Qiufeng Wang, Lihong Zhi, Jia Li and Wenda Li},
year = {2026},
doi = {10.48550/arxiv.2601.14027},
eprint = {2601.14027},
archivePrefix = {arXiv},
url = {https://doi.org/10.48550/arxiv.2601.14027}
}References
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