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patissierMongs

Dice MCP Server

by patissierMongs
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Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v4.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: clear_history manages session history, get_history retrieves it, reroll repeats the last roll, roll_dice handles standard dice notation, and roll_pool focuses on pool-based systems. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with clear, descriptive verbs (clear, get, reroll, roll) and specific nouns (history, dice, pool). The naming is uniform and predictable across all five tools.

    Tool Count5/5

    With 5 tools, this server is well-scoped for dice rolling and session management. Each tool serves a distinct and necessary function, covering core operations without bloat or redundancy.

    Completeness5/5

    The toolset provides complete coverage for dice rolling domains: session history management (clear and get), roll repetition (reroll), standard dice mechanics (roll_dice), and pool-based systems (roll_pool). There are no obvious gaps for typical TRPG or dice-based workflows.

  • Average 3.5/5 across 5 of 5 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

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