Occam

Occam finds the simplest equation consistent with your data.

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Occam is an MCP server that discovers mathematical equations from numerical data. Give it measurements, get back governing equations — ranked by the tradeoff between simplicity and accuracy.

Tools

Tool	Method	Speed	Best for
run_sindy	Sparse Identification of Nonlinear Dynamics	seconds	Differential equations from time series
run_pysr	Evolutionary symbolic regression	10–60s	Algebraic relationships (Pareto front)

Examples

SINDy — discover a dynamical system

Given time series of the Lorenz attractor, Occam recovers the governing equations:

dx/dt = -10.0 x + 10.0 y
dy/dt =  28.0 x -  1.0 y - 1.0 x z
dz/dt =  -2.667 z + 1.0 x y

PySR — find an algebraic law

Given noisy observations of a physical relationship, Occam returns a Pareto front trading complexity against accuracy:

Complexity  Loss       Expression
1           3.41       1.4
3           0.92       sin(x) * y
5           0.003      sin(x) * y + 1.4

Limits (free tier)

Parameter	run_sindy	run_pysr
Max rows	10,000	1,000
Max variables / features	20	10
Wall clock timeout	30s	60s
Rate limit (per IP)	10 requests / hour
Rate limit (global)	30 requests / hour

Connect

Connect any MCP client to the remote endpoint:

https://occam.fit/mcp/

Or in claude_desktop_config.json:

{
  "mcpServers": {
    "occam": {
      "type": "streamable-http",
      "url": "https://occam.fit/mcp/"
    }
  }
}

How it works

SINDy uses PySINDy to fit sparse linear combinations of candidate library functions to numerical derivatives. It runs in-process in Python and returns results in seconds.

PySR delegates to a pool of pre-warmed Julia workers running SymbolicRegression.jl v2. It evolves a population of candidate expressions and returns the Pareto-optimal set — every expression that is the best known at its complexity level.