# com.moltlinestudio/data (remote · mcp.moltlinestudio.com)

Hosted MCP server for data analysis: CSV profiling, A/B tests, cohorts, funnels, trend forecasts.

- Trust score: 70/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-17

## Components

- remote · `mcp.moltlinestudio.com`: 70/100 (this document), [markdown](https://verifymcp.io/servers/com-moltlinestudio-data/data.md), [page](https://verifymcp.io/servers/com-moltlinestudio-data/data)

## Channel facts

- Endpoint: `https://mcp.moltlinestudio.com/data`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-17.

- **Endpoint Security**: 83/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC is configured correctly; the domain's records validate against the full chain to the root.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 60/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 1709 tokens (~244/item across 7 items; 7 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: not enough scan history yet (needs a 30-day window).
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

**Unverified: 1 category.** A category scored 0 because we could not verify it: authentication we do not have, an unreachable endpoint, or not enough scan history. We only credit what we can confirm.

## Install

### Claude

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

### Codex

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

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-moltlinestudio-data": {
      "type": "remote",
      "url": "https://mcp.moltlinestudio.com/data",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-moltlinestudio-data --url https://mcp.moltlinestudio.com/data --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-moltlinestudio-data:
    url: "https://mcp.moltlinestudio.com/data"
```

### Other

```json
{
  "mcpServers": {
    "com-moltlinestudio-data": {
      "type": "http",
      "url": "https://mcp.moltlinestudio.com/data"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-17 (score 70)

First indexed and scored.

## MCP tools (7)

### `csv_profile` (~260 tokens)

Csv Profile

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, "unique": 2, "min": 29, ...}},
"quality_flags": ["..."], "note": "first 2000 rows profiled"}. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "delimiter must be a single character, e.g. ',' or ';'"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input parameters:

- `csv_text` (string, required): Raw CSV content including a header row, pasted as a single string; the first 2000 data rows are profiled.
- `delimiter` (string): Field separator, exactly one character, e.g. "," or ";". Default ",".

### `ab_test` (~292 tokens)

Ab Test

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"}. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need visitors > 0 and 0 <= conversions <= visitors"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input parameters:

- `conversions_a` (integer, required): Conversions in variant A; 0 or more, at most visitors_a.
- `conversions_b` (integer, required): Conversions in variant B; 0 or more, at most visitors_b.
- `visitors_a` (integer, required): Visitors in variant A; must be at least 1.
- `visitors_b` (integer, required): Visitors in variant B; must be at least 1.

### `correlation` (~214 tokens)

Correlation

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": "..."}. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need two equal-length series of 3+ values"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input parameters:

- `x` (array, required): First numeric series; at least 3 values, same length as y.
- `y` (array, required): Second numeric series; at least 3 values, same length as x.

### `growth_rates` (~188 tokens)

Growth Rates

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}. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need at least 2 values"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input parameters:

- `values` (array, required): Ordered numeric series, oldest first, at least 2 values, e.g. monthly revenue [1000, 1100, 1320].

### `funnel_report` (~225 tokens)

Funnel Report

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": "..."}. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need at least 2 stages"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input parameters:

- `stages` (object, required): 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}.

### `cohort_retention` (~264 tokens)

Cohort Retention

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": "..."}. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "cohort '<value>' must map to a list of numbers,"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input parameters:

- `cohorts` (object, required): 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_trend` (~224 tokens)

Forecast Trend

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": "..."}. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need at least 4 historical values"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input parameters:

- `periods_ahead` (integer): How many future periods to forecast; values outside 1-12 are clamped. Default 3.
- `values` (array, required): Ordered historical series, oldest first; at least 4 values.

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-moltlinestudio-data/data#diagnostics

## Score history

- 2026-08-17: 70

## Links

- Remote endpoint: https://mcp.moltlinestudio.com/data
- Repository: https://github.com/GarphenGate/moltline-mcp
- Website: https://moltlinestudio.com/
- Changelog RSS feed: https://verifymcp.io/servers/com-moltlinestudio-data/data.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-moltlinestudio-data/data.json
- HTML version of this page: https://verifymcp.io/servers/com-moltlinestudio-data/data