MCP server that wraps the Dagster GraphQL API — manage runs, assets, schedules, sensors, and backfills from any MCP client
Nothing to run from here
Moltline Data Desk 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.
7
tools declared
—
trust score
remote
at its publisher
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calls last 7d
What it does
Paste-your-data analytics: CSV profiling, A/B tests, correlation, growth. 4 of 7 free.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http moltline-data-desk-mcp https://mcp.moltlinestudio.com/data
# 2 — ask your agent for something these tools do
# csv_profile, ab_test, correlation and 4 more
Moltline Data Desk costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
MOAll 22 servers
moltlinestudio22 servers
15 categories
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 moltline-data-desk-mcp https://mcp.moltlinestudio.com/dataReconnect, 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
7 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.
Profile pasted CSV data column by column with data-quality flags. FREE. Reports per-column type, null rate, unique count, numeric stats (min/mean/max), and top values. Typical input {"csv_text": "name,age Ada,36 Lin,29"} returns {"rows": 2, "columns": {"age": {"type": "numeric", "null_pct": 0.0, "unique": 2, "min": 29, ...}}, "quality_flags": ["..."], "note": "first 2000 rows profiled"}. Use a
| Parameter | Type | Required | Notes |
|---|---|---|---|
| csv_text | string | yes | Raw CSV content including a header row, pasted as a single string; the first 2000 data rows are profiled. |
| delimiter | string | no | Field separator, exactly one character, e.g. "," or ";". Default ",". |
Run a two-proportion A/B significance test with a plain-language verdict. FREE. Typical input {"conversions_a": 120, "visitors_a": 2400, "conversions_b": 156, "visitors_b": 2380} returns {"rate_a_pct": 5.0, "rate_b_pct": 6.55, "relative_lift_pct": 31.1, "z_score": ..., "p_value": ..., "significant_at_95": true, "verdict": "B beats A — statistically significant"}. Use when exactly two variants ea
| Parameter | Type | Required | Notes |
|---|---|---|---|
| conversions_a | integer | yes | Conversions in variant A; 0 or more, at most visitors_a. |
| visitors_a | integer | yes | Visitors in variant A; must be at least 1. |
| conversions_b | integer | yes | Conversions in variant B; 0 or more, at most visitors_b. |
| visitors_b | integer | yes | Visitors in variant B; must be at least 1. |
Compute the Pearson correlation between two numeric series. FREE. Typical input {"x": [1, 2, 3, 4], "y": [2.1, 3.9, 6.2, 8.1]} returns {"pearson_r": 0.999, "r_squared": 0.998, "interpretation": "very strong positive correlation", "caution": "..."}. Use when two equal-length numeric series may move together. Reports association only, never causation. Not for a single series over time (growth_rate
| Parameter | Type | Required | Notes |
|---|---|---|---|
| x | array | yes | First numeric series; at least 3 values, same length as y. |
| y | array | yes | Second numeric series; at least 3 values, same length as x. |
Compute period-over-period growth and CAGR for a numeric series. FREE. Typical input {"values": [1000, 1100, 1320]} returns {"period_over_period_pct": [10.0, 20.0], "total_change_pct": 32.0, "avg_growth_per_period_pct_cagr": 14.89}. Use when one series is already in period order. Not for comparing two variants (ab_test) and not for projecting future periods (forecast_trend). Errors: on invalid,
| Parameter | Type | Required | Notes |
|---|---|---|---|
| values | array | yes | Ordered numeric series, oldest first, at least 2 values, e.g. monthly revenue [1000, 1100, 1320]. |
Analyze a conversion funnel and find the biggest drop-off. PREMIUM (license). Typical input {"stages": {"Visited": 1000, "Signed up": 200, "Paid": 50}} returns {"steps": [{"from": "Visited", "to": "Signed up", "conversion_pct": 20.0, "lost": 800}, ...], "overall_conversion_pct": 5.0, "biggest_dropoff": {...}, "recommendation": "..."}. Use when stage counts descend through one funnel. Not for ret
| Parameter | Type | Required | Notes |
|---|---|---|---|
| stages | object | yes | Ordered mapping of stage name to count, top of funnel first; at least 2 stages with non-negative numeric values, e.g. {"Visited": 1000, "Signed up": 200}. |
Build a retention table and average curve from raw cohort counts. PREMIUM (license). Typical input {"cohorts": {"2026-01": [1000, 400, 300, 250]}} — index 0 is cohort size, each later index is users still active in that period — returns {"retention_table_pct": {"2026-01": [100.0, 40.0, 30.0, 25.0]}, "avg_curve_pct": [...], "reading": "..."}. Use when each cohort has counts per period since acqui
| Parameter | Type | Required | Notes |
|---|---|---|---|
| cohorts | object | yes | Mapping of cohort label to a list of counts, where counts[0] is the cohort size and counts[n] is users active in period n, e.g. {"2026-01": [1000, 400, 300]}. The first 24 cohorts are used. |
Forecast future periods with a linear trend and honest fit quality. PREMIUM (license). For quick planning, not statistical modeling. Typical input {"values": [100, 120, 138, 161], "periods_ahead": 3} returns {"trend_per_period": 20.2, "r_squared": 0.998, "forecast": [180.9, 201.1, 221.3], "caveat": "..."}. Use when a series is roughly linear and fit quality matters as much as the projection. Not
| Parameter | Type | Required | Notes |
|---|---|---|---|
| values | array | yes | Ordered historical series, oldest first; at least 4 values. |
| periods_ahead | integer | no | How many future periods to forecast; values outside 1-12 are clamped. Default 3. |
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 Moltline Data Desk or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
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 1.2.0.
1.2.0
undated
latestNo release note was published with this version.
—
no reviews yet
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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.
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Any signed-in account that does not publish Moltline Data Desk 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.