decisionmatrix-mcp
Deterministic multi-criteria decision analysis for AI agents — score, rank & explain options.
Sollte ich dies verwenden
Qualität und Sicherheit
Befunde (2)
- LOWTool 'compare_two' description lacks action verbin compare_two
- LOWTool 'health_check' description lacks action verbin health_check
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": {
"decisionmatrix-mcp": {
"command": "npx",
"args": [
"decisionmatrix-mcp"
]
}
}
}Ausführbare Pakete
1.0.2stdioRemote-Endpunkte
https://decisionmatrix-mcp.pages.dev/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (6)
🟡create_decision(options, criteria, scores, method)
Rank named options against weighted criteria and return the winner, full ranking, per-criterion score breakdowns, methodology, the weights used, and a plain-language explanation. This is the main tool. Provide options, criteria [{name, weight, direction}], and a scores matrix. method defaults to weighted_sum (also: weighted_product, topsis). 100% deterministic.
Eingabe-Schema
{
"type": "object",
"properties": {
"options": {
"type": "array",
"description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}].",
"items": {
"type": [
"string",
"object"
]
}
},
"criteria": {
"type": "array",
"description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"weight": {
"type": "number"
},
"direction": {
"type": "string",
"enum": [
"benefit",
"cost"
],
"default": "benefit"
}
},
"required": [
"name",
"weight"
]
}
},
"scores": {
"description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object.",
"type": "object"
},
"method": {
"type": "string",
"enum": [
"weighted_sum",
"weighted_product",
"topsis"
],
"default": "weighted_sum"
}
},
"required": [
"options",
"criteria",
"scores"
]
}🟡score_options(options, criteria, scores, method)
Score options against criteria when the score matrix is supplied separately. Returns the full normalized scored matrix (per-option, per-criterion) plus a ranking, without the narrative winner explanation. Use create_decision if you want a winner + explanation.
Eingabe-Schema
{
"type": "object",
"properties": {
"options": {
"type": "array",
"description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}].",
"items": {
"type": [
"string",
"object"
]
}
},
"criteria": {
"type": "array",
"description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"weight": {
"type": "number"
},
"direction": {
"type": "string",
"enum": [
"benefit",
"cost"
],
"default": "benefit"
}
},
"required": [
"name",
"weight"
]
}
},
"scores": {
"description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object.",
"type": "object"
},
"method": {
"type": "string",
"enum": [
"weighted_sum",
"weighted_product",
"topsis"
],
"default": "weighted_sum"
}
},
"required": [
"options",
"criteria",
"scores"
]
}⚪sensitivity_analysis(options, criteria, scores, method, variation, ...)
Test how robust the winner is to changes in criteria weights. Sweeps each criterion's weight +/- 'variation' (default 0.2 = 20%) over 'steps' (default 10) increments, recomputes the ranking, and reports a robustness score, which criteria are most likely to flip the result, and the flip points.
Eingabe-Schema
{
"type": "object",
"properties": {
"options": {
"type": "array",
"description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}].",
"items": {
"type": [
"string",
"object"
]
}
},
"criteria": {
"type": "array",
"description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"weight": {
"type": "number"
},
"direction": {
"type": "string",
"enum": [
"benefit",
"cost"
],
"default": "benefit"
}
},
"required": [
"name",
"weight"
]
}
},
"scores": {
"description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object.",
"type": "object"
},
"method": {
"type": "string",
"enum": [
"weighted_sum",
"weighted_product",
"topsis"
],
"default": "weighted_sum"
},
"variation": {
"type": "number",
"default": 0.2,
"description": "Fractional weight sweep, 0<v<=1. 0.2 = +/-20%."
},
"steps": {
"type": "integer",
"default": 10,
"description": "Number of weight steps per criterion (2-100)."
}
},
"required": [
"options",
"criteria",
"scores"
]
}⚪compare_two(option_a, option_b, options, criteria, scores, ...)
Direct head-to-head comparison of exactly two options. Returns the winner, the score margin, how many criteria each option wins, and a per-criterion breakdown of who each criterion favours. Pass option_a and option_b (names) or a 2-element options array, plus criteria and scores.
Eingabe-Schema
{
"type": "object",
"properties": {
"option_a": {
"type": "string"
},
"option_b": {
"type": "string"
},
"options": {
"type": "array",
"description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}].",
"items": {
"type": [
"string",
"object"
]
}
},
"criteria": {
"type": "array",
"description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"weight": {
"type": "number"
},
"direction": {
"type": "string",
"enum": [
"benefit",
"cost"
],
"default": "benefit"
}
},
"required": [
"name",
"weight"
]
}
},
"scores": {
"description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object.",
"type": "object"
},
"method": {
"type": "string",
"enum": [
"weighted_sum",
"weighted_product",
"topsis"
],
"default": "weighted_sum"
}
},
"required": [
"criteria",
"scores"
]
}🟢list_methods
List the available scoring methods (weighted_sum, weighted_product, topsis) with descriptions, normalization details, score ranges, and when to use each. No parameters.
Eingabe-Schema
{
"type": "object",
"properties": {}
}🟢health_check
Server health, version, and capabilities. No parameters.
Eingabe-Schema
{
"type": "object",
"properties": {}
}Community
Nachweis