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Security, Science & HardwareAny

Give agents a multi-engine math kernel via MCP

MathKernel is an evidence-aware multi-engine mathematics kernel exposed as an MCP server for agents to use.

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Use case overview

MathKernel is an evidence-aware multi-engine mathematics kernel exposed as an MCP server for agents to use.

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Reported experience

  1. What they did

    MathKernel runs as an MCP server (mathkernel-mcp, stdio, 162 math_ tools). The model parses and plans, and the kernel does the computing across SymPy, Z3, Lean, mpmath and numba/CUDA. A typical session discovers capabilities, parses an expression, creates a context, then calls math_reason to solve and verify. Long sweeps go through async jobs. Every result carries a trust label and a derivation trail.

  2. How it went

    The source gives no benchmark or outcome numbers. It documents the design: trust is capped at the weakest evidence, and decimal inputs drop a result to numeric, which blocks Lean and SMT proofs.

  3. Worth knowing

    Lean 4 and Mathlib install on first server start unless MATHKERNEL_SKIP_LEAN_INSTALL=1 is set. CUDA needs the extra nvidia pip packages, otherwise it falls back to CPU.

Example prompts

Try with Claude Code
Connect the MCP server for [math tool, e.g. MathKernel or a computer algebra system] to this project, then use it to solve [math problem or set of equations] and show the result along with which engine produced it and how it was verified. If engines disagree, flag it and explain. Done means I get the answer, the evidence for it, and a note on any assumptions you made.

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