MCP server

Moltline Data Desk

com.moltlinestudio/data

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Paste-your-data analytics: CSV profiling, A/B tests, correlation, growth. 4 of 7 free.

Working at last checkVerified publisher: moltlinestudio.comAbout 2,498 tokens per request once connected7 tools

Website Source

https://mcp.moltlinestudio.com/data

At a glance

Type: MCP server
Publisher: moltlinestudio.com (verified by the MCP Registry)
Status: Working at last check
Tools: 7
Token cost: About 2,498 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http data https://mcp.moltlinestudio.com/data

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.data]
url = "https://mcp.moltlinestudio.com/data"

Gemini CLI

{"mcpServers":{"data":{"httpUrl":"https://mcp.moltlinestudio.com/data"}}}

Cursor

{"mcpServers":{"data":{"url":"https://mcp.moltlinestudio.com/data"}}}

VS Code

{"servers":{"data":{"type":"http","url":"https://mcp.moltlinestudio.com/data"}}}

Antigravity

agy mcp add data https://mcp.moltlinestudio.com/data

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"data","server_url":"https://mcp.moltlinestudio.com/data","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"data","server_url":"https://mcp.moltlinestudio.com/data"}

Tools

ab_test ~438 tokens
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_
cohort_retention ~346 tokens
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]},
correlation ~331 tokens
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
csv_profile ~390 tokens
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\nAda,36\nLin,29"} returns {"rows": 2, "columns": {"age": {"type": "numeric", "null_pct": 0.0,
forecast_trend ~360 tokens
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":
funnel_report ~342 tokens
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_dropo
growth_rates ~291 tokens
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

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