MCP server that wraps the Dagster GraphQL API — manage runs, assets, schedules, sensors, and backfills from any MCP client
Nothing to run from here
Occam is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
4
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Finds the simplest equation consistent with your data. SINDy and PySR symbolic regression via MCP.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http occam-mcp https://occam.fit/mcp/
# 2 — ask your agent for something these tools do
# feature_request, sindy_run, pysr_run and 1 more
Occam costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
OCAll 1 server
occam1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http occam-mcp https://occam.fit/mcp/Reconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
4 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
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 flooding. Descriptions longer than 500 characters are truncated.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| description | string | yes | A short description of the feature you need. Examples: 'LaTeX output for equations', 'support for ODE constraints', 'GPU-accelerated search', 'larger dataset limits'. Helps prioritize development. |
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 tier up to 100 rows and 8 variables. Beyond that, $0.05 + $0.01 per 100 extra rows +
| Parameter | Type | Required | Notes |
|---|---|---|---|
| data | array | yes | 2D array of time series data. Each row is a timestep, each column is a state variable. Minimum 3 rows (finite-difference derivative). Free tier: 100 rows, 8 variables. Paid tier: up to 500,000 rows, 5 |
| t | array | yes | Timestamps corresponding to each row of data. Length must match row count. |
| feature_names | no | Names for each variable/feature column. Defaults to x0, x1, ... | |
| poly_degree | integer | no | Polynomial library degree for SINDy candidate functions. Default 2. |
| threshold | number | no | STLSQ sparsity threshold. Higher values produce sparser equations. Default 0.1. |
| max_iter | integer | no | Maximum STLSQ optimizer iterations. Default 20. |
| payment | no | 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 objects, so the object form is canonical |
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 series, use sindy_run instead. Pricing: free tier up to 100 rows × 8 features,
| Parameter | Type | Required | Notes |
|---|---|---|---|
| X | array | yes | 2D array of input features. Each row is an observation, each column is a feature. Minimum 5 rows. Free tier: 100 rows, 8 features. Paid tier: up to 50,000 rows, 20 features. |
| y | array | yes | Target values, one per row of X. |
| feature_names | no | Names for each variable/feature column. Defaults to x0, x1, ... | |
| unary_operators | no | 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) = 1/x') are NOT supported — only the name | |
| binary_operators | no | Allowed binary operators, drawn from the fixed supported set: +, -, *, /, ^. Custom operators are NOT supported. Default: +, -, *, /. Pass [] for none. | |
| max_complexity | integer | no | Maximum expression tree size. Higher allows more complex expressions. Default 20, max 25. |
| populations | integer | no | Number of evolutionary populations for the search. Default 15, max 20. |
| timeout_seconds | integer | no | Wall clock time limit in seconds. Free tier: max 60. Paid tier: max 300 (5 minutes). Default 60. |
| loss_threshold | no | 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, even if the timeout has not been reached. | |
| stall_detection | boolean | no | 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 reclaims compute once the search has converged. |
| payment | no | 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 objects, so the object form is canonical |
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 fit constants. Returns frequentist bootstrap confidence intervals, not Bayesian c
| Parameter | Type | Required | Notes |
|---|---|---|---|
| expression | string | yes | 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 parameters — integers in the expression (e. |
| X | array | yes | 2D array of input features. Each row is an observation, each column is a feature. Minimum 5 rows. Free tier: 100 rows, 8 features. Paid tier: up to 50,000 rows, 20 features. |
| y | array | yes | Target values, one per row of X. |
| feature_names | no | Names for each variable/feature column. Defaults to x0, x1, ... | |
| y_sigma | no | Optional per-point measurement standard deviations, or a single scalar applied to all points. When supplied, the helper uses parametric bootstrap (y_b = y + Normal(0, y_sigma)); otherwise it uses resi | |
| n_resamples | integer | no | Number of bootstrap resamples. Higher = tighter CIs, more compute. Default 100. |
| alpha | number | no | Significance level. 0.05 → 95%% CI. Default 0.05. |
| x_grid | no | 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. |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Occam or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 0.1.1.
0.1.1
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Occam can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
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Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.