Koskamo

DecisionMatrix MCP

A deterministic, stateless MCP server that performs multi-criteria decision analysis for AI agents. It accepts options and weighted criteria to return fully scored, ranked, and explainable results using methods like Weighted Sum, Weighted Product, and TOPSIS, including sensitivity analysis and per-criterion breakdowns.

Endpoint and access

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DecisionMatrix MCP logo, by inity13Community listingStreamable HTTPNo sign-inEndpoint checked 2026-11-07Published by inity13
MCP endpoint (Streamable HTTP)
https://decisionmatrix-mcp.pages.dev/mcp
Vendor documentation

What its tools do

6 tools, grouped by the hints the server advertises. Hints are self-declared, not verified behavior.

Not annotated (6)

6 of 6 have a description · 0 of 6 declare behavior hints · 0 of 4 with parameters document them all

Checks and signals

Each line is separate evidence, not a trust score.

  • Passed Endpoint answered the live check ·
  • Availability 1 of 1 checks passed in 30 days

What you can do with it

  • Rank options against weighted criteria to find a winner
  • Perform sensitivity analysis on decision weights
  • Compare two options head-to-head with per-criterion breakdowns
  • Discover available scoring methods and their use cases

Source and maintenance

Community listingRegistry 1.0.2
mcp-registry: io.github.inity13/decisionmatrix-mcp@1.0.2Source repository
Maintenance checked

Protocol and capabilities

Server
DecisionMatrix 1.0.0-edge
MCP protocol negotiated in check
2025-11-25
Tools
6 advertised
Resources
Not advertised
Resource templates
Not advertised
Prompts
Not advertised
Server-advertised capabilities
{
  "tools": {
    "listChanged": false
  }
}

Tools

6 advertised

create_decision
Advertised by the server during the last successful anonymous check.

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.

create_decision input schema
{
  "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)}."
    }
  }
}
score_options
Advertised by the server during the last successful anonymous check.

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.

score_options input schema
{
  "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)}."
    }
  }
}
sensitivity_analysis
Advertised by the server during the last successful anonymous check.

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.

sensitivity_analysis input schema
{
  "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%."
    }
  }
}
compare_two
Advertised by the server during the last successful anonymous check.

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.

compare_two input schema
{
  "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"
    }
  }
}
list_methods
Advertised by the server during the last successful anonymous check.

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

list_methods input schema
{
  "type": "object",
  "properties": {}
}
health_check
Advertised by the server during the last successful anonymous check.

Server health, version, and capabilities. No parameters.

health_check input schema
{
  "type": "object",
  "properties": {}
}

Prompts

Not advertised

No prompt definitions available.

Resources

Not advertised

No resource definitions available.

30-day availability

Aggregated from read-only remote checks; this is not a tool-execution or security guarantee.

Successful checks
1 of 1 (100%)
Average latency
435 ms
95th percentile latency
435 ms

Maintenance history

Public check and source-refresh events. Editorial and ownership records remain private.

  • · probe · passed · 435 ms · metadata changed · 6 tool(s)

Connect from your client

Each snippet registers the same endpoint; pick the client you use.

This server is operated by the named third party. Listing and endpoint checks are not an endorsement or a security audit. Review the operator's permissions, terms, and data handling before connecting. How listings are checked and corrected.

Claude Code

Run this once in a terminal. It registers the remote server. Use --scope project to write .mcp.json for the repo.
Claude Code configuration
claude mcp add --transport http decisionmatrix-mcp-pages https://decisionmatrix-mcp.pages.dev/mcp

Codex

Run this once. Codex stores MCP servers in ~/.codex/config.toml (or .codex/config.toml in a trusted project).
Codex configuration
codex mcp add decisionmatrix-mcp-pages --url https://decisionmatrix-mcp.pages.dev/mcp

Cursor

Merge this server into .cursor/mcp.json in your project, then enable decisionmatrix-mcp-pages in your MCP settings.
Cursor configuration
{
  "mcpServers": {
    "decisionmatrix-mcp-pages": {
      "url": "https://decisionmatrix-mcp.pages.dev/mcp"
    }
  }
}

Cline

Merge this into cline_mcp_settings.json (Cline → MCP Servers → Configure).
Cline configuration
{
  "mcpServers": {
    "decisionmatrix-mcp-pages": {
      "type": "streamableHttp",
      "url": "https://decisionmatrix-mcp.pages.dev/mcp",
      "disabled": false
    }
  }
}

VS Code

Merge this server into .vscode/mcp.json. Use MCP: List Servers to start decisionmatrix-mcp-pages and inspect its tools.
VS Code configuration
{
  "servers": {
    "decisionmatrix-mcp-pages": {
      "type": "http",
      "url": "https://decisionmatrix-mcp.pages.dev/mcp"
    }
  }
}

Gemini CLI

Run this once. It writes .gemini/settings.json in the current project; pass --scope user for ~/.gemini/settings.json.
Gemini CLI configuration
gemini mcp add --transport http decisionmatrix-mcp-pages https://decisionmatrix-mcp.pages.dev/mcp

Claude Desktop

Open Claude Settings > Connectors > Add custom connector, enter this server URL and enable it for the conversation. This is a manual remote-connector handoff, not a desktop JSON configuration.
Claude Desktop configuration
https://decisionmatrix-mcp.pages.dev/mcp

Windsurf

Merge this into ~/.codeium/windsurf/mcp_config.json, then refresh MCP in Cascade. Windsurf remote servers use serverUrl, not url.
Windsurf configuration
{
  "mcpServers": {
    "decisionmatrix-mcp-pages": {
      "serverUrl": "https://decisionmatrix-mcp.pages.dev/mcp"
    }
  }
}

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