Finds the simplest equation consistent with your data. SINDy and PySR symbolic regression via MCP.
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https://occam.fit/mcp/4 strumenti · 90 msfeature_requestRequest a feature that Occam doesn't support yet.
Use this when you need a capability that Occam doesn't currently
offer. Requests are logged and used to prioritize development.
Rate limit: 5 requests/hour per IP, 50/hour global — stricter than
the compute tools' 10/hour to prevent log floodi…Request a feature that Occam doesn't support yet. Use this when you need a capability that Occam doesn't currently offer. Requests are logged and used to prioritize development. Rate limit: 5 requests/hour per IP, 50/hour global — stricter than the compute tools' 10/hour to prevent log floodi…
| Parametro | Tipo | Descrizione |
|---|---|---|
| description* | string | A short description of the feature you need. Examples: 'LaTeX output for equations', 'support for ODE constraints', 'GPU-accelerated search', 'larger dataset l… |
sindy_runSparse Identification of Nonlinear Dynamics (SINDy).
Recovers governing differential equations (dx/dt = f(x)) from time
series data. Returns human-readable sparse expressions. Fast (seconds).
For algebraic y = f(x) relationships without time structure, use
pysr_run instead.
Pricing: free tie…Sparse Identification of Nonlinear Dynamics (SINDy). Recovers governing differential equations (dx/dt = f(x)) from time series data. Returns human-readable sparse expressions. Fast (seconds). For algebraic y = f(x) relationships without time structure, use pysr_run instead. Pricing: free tie…
| Parametro | Tipo | Descrizione |
|---|---|---|
| data* | array | 2D array of time series data. Each row is a timestep, each column is a state variable. Free tier: 100 rows, 8 variables. Paid tier: up to 500,000 rows, 50 vari… |
| t* | array | Timestamps corresponding to each row of data. Length must match row count. |
| feature_names | — | Names for each variable/feature column. Defaults to x0, x1, ... |
| poly_degree | integer | Polynomial library degree for SINDy candidate functions. Default 2. |
| threshold | number | STLSQ sparsity threshold. Higher values produce sparser equations. Default 0.1. |
| max_iter | integer | Maximum STLSQ optimizer iterations. Default 20. |
| payment | — | Payment credential. Accepts either a JSON object or a JSON-encoded string (FastMCP's transport pre-parses strings whose field annotation is non-bare-`str` into… |
pysr_runEvolutionary Symbolic Regression (PySR).
Discovers algebraic equations y = f(x1, x2, ...) from feature/target
data. Returns a Pareto front ranked by the complexity/accuracy
tradeoff. Slower than SINDy (10-60s); searches often terminate early
on convergence. For differential equations from time…Evolutionary Symbolic Regression (PySR). Discovers algebraic equations y = f(x1, x2, ...) from feature/target data. Returns a Pareto front ranked by the complexity/accuracy tradeoff. Slower than SINDy (10-60s); searches often terminate early on convergence. For differential equations from time…
| Parametro | Tipo | Descrizione |
|---|---|---|
| X* | array | 2D array of input features. Each row is an observation, each column is a feature. Free tier: 100 rows, 8 features. Paid tier: up to 50,000 rows, 20 features. |
| y* | array | Target values, one per row of X. |
| feature_names | — | Names for each variable/feature column. Defaults to x0, x1, ... |
| unary_operators | — | Allowed unary operators, drawn from the fixed supported set: sin, cos, tan, exp, log, log2, log10, sqrt, abs, sinh, cosh, tanh. Custom operators (e.g. 'inv(x)… |
| binary_operators | — | Allowed binary operators, drawn from the fixed supported set: +, -, *, /, ^. Custom operators are NOT supported. Default: +, -, *, /. Pass [] for none. |
| max_complexity | integer | Maximum expression tree size. Higher allows more complex expressions. Default 20, max 25. |
| populations | integer | Number of evolutionary populations for the search. Default 15, max 20. |
| timeout_seconds | integer | Wall clock time limit in seconds. Free tier: max 60. Paid tier: max 300 (5 minutes). Default 60. |
| loss_threshold | — | Optional early-stop threshold on the best loss found. If set, the search terminates as soon as any Pareto-front member reaches a loss at or below this value, e… |
| stall_detection | boolean | When true (default), the server stops the search early if the best loss has not improved by more than 1% during the last third of the time budget. This reclaim… |
| payment | — | Payment credential. Accepts either a JSON object or a JSON-encoded string (FastMCP's transport pre-parses strings whose field annotation is non-bare-`str` into… |
pysr_uncertaintyBootstrap confidence intervals for the numeric constants of a
frozen expression, plus optional prediction bands on an x-grid.
Typical flow: call pysr_run, pick an expression from the response
(best_expression or a pareto_front entry), pass it back here with
the same dataset to get CIs on its f…Bootstrap confidence intervals for the numeric constants of a frozen expression, plus optional prediction bands on an x-grid. Typical flow: call pysr_run, pick an expression from the response (best_expression or a pareto_front entry), pass it back here with the same dataset to get CIs on its f…
| Parametro | Tipo | Descrizione |
|---|---|---|
| expression* | string | The expression to bootstrap, as returned by pysr_run (`best_expression` or a `pareto_front[i].expression`). Only numeric Float constants are treated as free pa… |
| X* | array | 2D array of input features. Each row is an observation, each column is a feature. Free tier: 100 rows, 8 features. Paid tier: up to 50,000 rows, 20 features. |
| y* | array | Target values, one per row of X. |
| feature_names | — | Names for each variable/feature column. Defaults to x0, x1, ... |
| y_sigma | — | Optional per-point measurement standard deviations, or a single scalar applied to all points. When supplied, the helper uses parametric bootstrap (y_b = y + No… |
| n_resamples | integer | Number of bootstrap resamples. Higher = tighter CIs, more compute. Default 100. |
| alpha | number | Significance level. 0.05 → 95%% CI. Default 0.05. |
| x_grid | — | Optional 2D grid of feature values at which to report a prediction band. Must have the same number of columns as X. Omit to skip prediction-band computation. |
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Finds the simplest equation consistent with your data. SINDy and PySR symbolic regression via MCP.
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