Syl Pulse
Causal analytics: ask a business question, get a deterministic causal answer and charts.
Sollte ich dies verwenden
Qualität und Sicherheit
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"pulse": {
"url": "https://pulse.sylai.io/mcp"
}
}
}Remote-Endpunkte
https://pulse.sylai.io/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (1)
🟢pulse_analyze(question, csv, data, cause, effect, ...)
Estimate a causal effect from a dataset and answer a business question. Provide exactly one of ``csv`` (CSV text) or ``data`` (list of row objects). Returns the full long-form Pulse report (the same answer an email reply contains) as the primary text content and as ``report`` in the structured result, followed by chart PNGs as image content blocks (unless ``include_charts`` is false). Structured fields: the adjusted effect size (``ate``/``effect_size``) with its confidence interval (``ci_low``, ``ci_high``, ``ci_range``), per-channel effects (``channels``, keyed by outcome), confidence, and caveats. A ``test_design`` (how long a spend-cut test would take to confirm the effect, and whether the data already suffices) is included only when the question asks about sample size, power, or how long a test would take, or when ``include_test_design`` is true; otherwise it is null. With ``include_guardian_verdict`` it also returns ``guardian_verdict`` ``{verdict: pass|caution|hold, reason}``, computed locally. All numbers are deterministic statistics, never LLM-generated. Args: question: The business question, e.g. "Does ad spend drive sales?". csv: Dataset as CSV text. data: Dataset as a list of row records (alternative to ``csv``). cause: Treatment column (inferred from the question if omitted). effect: Outcome column (inferred if omitted). confounders: Columns to adjust for, in addition to those discovered. outcomes: Several outcome columns, for by-channel effects. time_col: Time column (used for the test-design cadence). include_guardian_verdict: Also return a pass/caution/hold verdict. include_charts: Attach chart images (DAG, effect, trend) as image content. include_test_design: Force the spend-cut test design / sample-size section on (true) or off (false). Omit (null) to include it only when the question asks about sample size, statistical power, or how long a test would take.
Eingabe-Schema
{
"type": "object",
"properties": {
"question": {
"title": "Question",
"type": "string"
},
"csv": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Csv"
},
"data": {
"anyOf": [
{
"items": {
"additionalProperties": true,
"type": "object"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Data"
},
"cause": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Cause"
},
"effect": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Effect"
},
"confounders": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Confounders"
},
"outcomes": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Outcomes"
},
"time_col": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Time Col"
},
"include_guardian_verdict": {
"default": false,
"title": "Include Guardian Verdict",
"type": "boolean"
},
"include_charts": {
"default": true,
"title": "Include Charts",
"type": "boolean"
},
"include_test_design": {
"anyOf": [
{
"type": "boolean"
},
{
"type": "null"
}
],
"default": null,
"title": "Include Test Design"
}
},
"required": [
"question"
],
"title": "pulse_analyzeArguments"
}Community
Nachweis