spec-score-mcp
Related Servers
Alternatives to spec-score-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityAmaintenanceEnables agents to score prose from 0-100 for formulaic AI writing tells using purely programmatic rule-based heuristics, with no LLM judge or API calls. Returns a numeric score, band label, specific violations with surrounding context, per-category counts, and concrete advice, and can also analyze a file path directly.-
- AlicenseNot gradedqualityDmaintenanceScores MCP tool definitions and tool lists from 0-100, flagging vague descriptions, missing parameter docs, non-verb-first naming, oversized enums, and nested schemas with severity, rationale, and concrete fixes. It also validates marketplace listings against platform character caps such as MCPize's 500-character short-description limit before deploy.MIT
- FlicenseNot gradedqualityAmaintenanceEnables agents to score prose from 0–100 for formulaic AI writing patterns using a purely rule-based linter, returning numeric scores, band labels, specific violations with context, and concrete advice. Also supports analyzing text files on disk directly.-
- FlicenseNot gradedqualityAmaintenanceEnables agents to analyze text or files and receive numeric slop scores, band labels, specific violations with context, and concrete writing advice, using rule-based diagnostics with no LLM judge or API calls.-
- FlicenseNot gradedqualityAmaintenanceScores text from 0 to 100 for formulaic AI writing patterns using configurable rule-based heuristics with no LLM judge or API calls. Enables agents to lint inline strings or files and receive a score, band, specific violations with context, and concrete advice.-
- AlicenseNot gradedqualityBmaintenanceEnables users to grade MCP tool definitions for agent-readiness, returning a score, A–F grade, concrete fixes, and estimated token cost.MIT
TDQS
Scored across 3 tools
The tools have overlapping purposes that could cause confusion. spec_score and spec_visualize both score a spec on the same four axes and provide the same analysis, making them nearly redundant. Only spec_compare has a clearly distinct function by comparing two specs, but the other two tools are ambiguous in their differentiation.
The naming follows a consistent pattern with all tools using the prefix 'spec_' followed by a verb (compare, score, visualize). This makes the purpose of each tool predictable and readable, though the similarity in naming between spec_score and spec_visualize contributes to the disambiguation issue.
With 3 tools, the count is reasonable for a server focused on spec evaluation. It covers core functions like scoring, comparing, and visualizing specs, which aligns well with the server's purpose, though the overlap between spec_score and spec_visualize suggests the set could be streamlined without losing functionality.
The tool surface is mostly complete for spec evaluation, covering scoring, comparison, and visualization. However, there is a notable gap in tools for editing or updating specs based on the analysis, which could limit workflow coverage. The redundancy between spec_score and spec_visualize also indicates inefficiency rather than a functional gap.