MCP Server Diff TypeScript
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as generating unified diffs between text articles, making it impossible to confuse with other tools.
Naming Consistency5/5The single tool name 'get-unified-diff' follows a clear verb-noun pattern (get + unified_diff). With only one tool, consistency is inherently perfect as there are no other names to compare against.
Tool Count2/5A single tool is generally too few for most server purposes, as it limits functionality and scope. While this server focuses narrowly on diff generation, having only one tool feels thin and may not cover related operations like diff analysis or formatting options.
Completeness3/5The tool provides a core diff generation function, but the surface is notably incomplete. There are obvious gaps, such as no tools for comparing files, handling different diff formats, or managing diff history, which limits the server's utility for broader text comparison tasks.
Average 3.1/5 across 1 of 1 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.
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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.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output format ('Unified diff format') but lacks details on error handling, performance characteristics, or any constraints (e.g., input size limits). For a tool with no annotations, this leaves significant gaps in understanding how it behaves beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core purpose and includes the output format, making it easy to understand quickly. Every part of the sentence contributes essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (comparing two strings) and no output schema, the description is adequate but incomplete. It covers the basic purpose and output format but lacks details on behavioral aspects like error cases or performance. Without annotations, it should do more to compensate, but it meets the minimum viable threshold for a simple diff tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for both parameters ('old string to compare' and 'new string to compare'). The description adds minimal value beyond the schema by implying the parameters are text articles, but it doesn't provide additional context like format expectations or examples. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the difference between two text articles in Unified diff format.' It specifies the verb ('Get'), resource ('difference'), and output format ('Unified diff format'), making the function unambiguous. However, since there are no sibling tools, it doesn't need to differentiate from alternatives, so it doesn't reach the highest score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It states what the tool does but offers no context about scenarios where it's appropriate, prerequisites, or limitations. With no sibling tools, it could implicitly suggest this is the only diff tool, but explicit usage guidelines are missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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