_ registry / mcp http-sse · checked 1h ago

DecisionMatrix

https://decisionmatrix-mcp.pages.dev

Registry code: 460a6f6f1c954c6d

api record

Deterministic multi-criteria decision analysis for AI agents — score, rank & explain options.

from a public catalogue that lists it, not from the operator

endpoint
https://decisionmatrix-mcp.pages.dev/mcp
protocol
http-sse ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is DecisionMatrix live?
Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.
Is DecisionMatrix free to use?
Yes — the hub reached it with no key and no payment.
What tools does DecisionMatrix have?
6 tools: create_decision, score_options, sensitivity_analysis, compare_two, health_check, list_methods.
Is DecisionMatrix safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
728ms

last good check

priced tools
0

of 6 tools

_ answered our checks, 90 days 573 checks · signed record
  • degraded → live
  • unknown → live
_ what it is for
topic
data & analytics
used for
  • rank options against weighted criteria
  • compare two options
  • run weight sensitivity analysis
takes → gives
data → data
tools
6 reads
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 6 tools
2 open 4 never probed 2 of 6 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • health_check reads open 6h ago

    Server health, version, and capabilities. No parameters.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • list_methods reads open 6h ago

    List the available scoring methods (weighted_sum, weighted_product, topsis) with descriptions, normalization details, score ranges, and when to use each. No parameters.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • create_decision reads unknown never probed

    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.

    mcp-tool

    {
  "type": "object",
  "required": [
    "options",
    "criteria",
    "scores"
  ],
  "properties": {
    "method": {
      "enum": [
        "weighted_sum",
        "weighted_product",
        "topsis"
      ],
      "type": "string",
      "default": "weighted_sum"
    },
    "scores": {
      "type": "object",
      "description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object."
    },
    "options": {
      "type": "array",
      "items": {
        "type": [
          "string",
          "object"
        ]
      },
      "description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}]."
    },
    "criteria": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name",
          "weight"
        ],
        "properties": {
          "name": {
            "type": "string"
          },
          "weight": {
            "type": "number"
          },
          "direction": {
            "enum": [
              "benefit",
              "cost"
            ],
            "type": "string",
            "default": "benefit"
          }
        }
      },
      "description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}."
    }
  }
}
    arguments 60 lines
  • score_options reads unknown never probed

    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.

    mcp-tool

    {
  "type": "object",
  "required": [
    "options",
    "criteria",
    "scores"
  ],
  "properties": {
    "method": {
      "enum": [
        "weighted_sum",
        "weighted_product",
        "topsis"
      ],
      "type": "string",
      "default": "weighted_sum"
    },
    "scores": {
      "type": "object",
      "description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object."
    },
    "options": {
      "type": "array",
      "items": {
        "type": [
          "string",
          "object"
        ]
      },
      "description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}]."
    },
    "criteria": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name",
          "weight"
        ],
        "properties": {
          "name": {
            "type": "string"
          },
          "weight": {
            "type": "number"
          },
          "direction": {
            "enum": [
              "benefit",
              "cost"
            ],
            "type": "string",
            "default": "benefit"
          }
        }
      },
      "description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}."
    }
  }
}
    arguments 60 lines
  • sensitivity_analysis reads unknown never probed

    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.

    mcp-tool

    {
  "type": "object",
  "required": [
    "options",
    "criteria",
    "scores"
  ],
  "properties": {
    "steps": {
      "type": "integer",
      "default": 10,
      "description": "Number of weight steps per criterion (2-100)."
    },
    "method": {
      "enum": [
        "weighted_sum",
        "weighted_product",
        "topsis"
      ],
      "type": "string",
      "default": "weighted_sum"
    },
    "scores": {
      "type": "object",
      "description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object."
    },
    "options": {
      "type": "array",
      "items": {
        "type": [
          "string",
          "object"
        ]
      },
      "description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}]."
    },
    "criteria": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name",
          "weight"
        ],
        "properties": {
          "name": {
            "type": "string"
          },
          "weight": {
            "type": "number"
          },
          "direction": {
            "enum": [
              "benefit",
              "cost"
            ],
            "type": "string",
            "default": "benefit"
          }
        }
      },
      "description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}."
    },
    "variation": {
      "type": "number",
      "default": 0.2,
      "description": "Fractional weight sweep, 0<v<=1. 0.2 = +/-20%."
    }
  }
}
    arguments 70 lines
  • compare_two reads unknown never probed

    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.

    mcp-tool

    {
  "type": "object",
  "required": [
    "criteria",
    "scores"
  ],
  "properties": {
    "method": {
      "enum": [
        "weighted_sum",
        "weighted_product",
        "topsis"
      ],
      "type": "string",
      "default": "weighted_sum"
    },
    "scores": {
      "type": "object",
      "description": "Score matrix. Object form: {\"Option A\": {\"Criterion 1\": 8, ...}, ...}. Array form: [{\"option\":\"Option A\",\"scores\":{...}}]. Or inline scores on each option object."
    },
    "options": {
      "type": "array",
      "items": {
        "type": [
          "string",
          "object"
        ]
      },
      "description": "Named alternatives. Strings [\"A\",\"B\"] or objects [{\"name\":\"A\",\"scores\":{...}}]."
    },
    "criteria": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name",
          "weight"
        ],
        "properties": {
          "name": {
            "type": "string"
          },
          "weight": {
            "type": "number"
          },
          "direction": {
            "enum": [
              "benefit",
              "cost"
            ],
            "type": "string",
            "default": "benefit"
          }
        }
      },
      "description": "Weighted criteria. Each: {name, weight (relative, >=0), direction: 'benefit' (higher better, default) | 'cost' (lower better)}."
    },
    "option_a": {
      "type": "string"
    },
    "option_b": {
      "type": "string"
    }
  }
}
    arguments 65 lines
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