kev-decision-mcp
Related Servers
Alternatives to kev-decision-mcp
No user-submitted related servers found.
Related Servers
- FlicenseAqualityCmaintenanceEnables an LLM client to perform basic arithmetic on two numbers — addition, subtraction, multiplication, and division — plus reverse a supplied text string, through five simple tools exposed over stdio. Inputs and structured text results follow JSON schemas, with invalid operations such as division by zero surfaced as tool errors.5-

faraztools-mcpofficial
AlicenseAqualityCmaintenanceEnables AI clients to call small utility tools like echo and Markdown-to-PDF conversion, running locally over stdio.2MIT- AlicenseAqualityAmaintenanceEnables MCP-compatible agent hosts to interact with TypeSafe AI's Jev System One API through dependency-free STDIO tools for classification, scoring, verification, gating, routing, review, and health checks.9MIT
- AlicenseNot gradedqualityBmaintenanceExposes code-review and issue-triage tools to AI assistants over stdio, letting them evaluate unified pull-request diffs for maintainer remarks, slice diffs into categorized AST hunks, and classify GitHub issues by priority while synthesizing minimal reproduction stubs.1Apache 2.0
- AlicenseAqualityCmaintenanceProvides AI clients with real-time tools for math evaluation, timezone-aware time lookup, live weather retrieval, and persistent note management, all accessible over the Model Context Protocol via stdio.6MIT
- AlicenseNot gradedqualityAmaintenanceEnables natural-language interaction with TypeSafe's Jev decision API, supporting mixed question calls, batch evaluation, model listing, and confidence or composite-score gates over stdio.7MIT
TDQS
Scored across 4 tools
Each tool has a distinct purpose: listing models, standard evaluation, order-sensitivity testing, and packed-vs-separate comparison. The three evaluation tools share a common foundation but are clearly differentiated by their constraints and outputs, though they could still be confused without careful reading.
All tools follow a consistent kev_<verb> snake_case pattern, making the set predictable and uniform. The verbs (list, evaluate, permute, separate) are domain-specific but consistently applied.
Four tools is well-scoped for a decision evaluation server. Each tool adds a distinct capability—model discovery, packed evaluation, order sensitivity, and independent evaluation—without redundancy or bloat.
The decision evaluation domain is fully covered: model metadata, packed evaluation supporting multiple question types, order-sensitivity checking, and independent evaluation for comparison. There are no obvious missing operations or dead ends for the stated purpose.