Connection check
verified live · 27h ago
decisionmatrix-mcp
Deterministic multi-criteria decision analysis for AI agents — score, rank & explain options.
Tools
6
GitHub stars
—
Installs / wk
52
Licence
MIT
Transport
streamable-http, stdio
Last checked
27h ago
Tools & capabilities
6 toolsRead from the running server on 27h ago.
compare_two
methodscores*optionscriteria*option_aoption_b
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… 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.
create_decision
methodscores*options*criteria*
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. T… 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.
health_check
Server health, version, and capabilities. No parameters. Server health, version, and capabilities. No parameters.
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. List the available scoring methods (weighted_sum, weighted_product, topsis) with descriptions, normalization details, score ranges, and when to use each. No parameters.
score_options
methodscores*options*criteria*
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 narra… 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.
sensitivity_analysis
stepsmethodscores*options*criteria*variation