Scrapbox MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap between tools, making disambiguation perfect. The tool's purpose is clearly defined and distinct by default.
Naming Consistency5/5The single tool follows a clear verb_noun pattern (get_page_content), and with no other tools to compare, consistency is inherently perfect. There are no deviations or mixed conventions.
Tool Count2/5One tool is too few for a server named 'Scrapbox MCP Server', which implies broader functionality for interacting with Scrapbox pages. A single fetch tool feels thin and limited in scope, suggesting an incomplete or minimal implementation.
Completeness2/5The tool surface is severely incomplete for a Scrapbox server, covering only fetching page content. Obvious gaps include creating, updating, deleting, or listing pages, which are essential operations for managing a wiki or note-taking system like Scrapbox.
Average 3.3/5 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
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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 full burden. It states the tool fetches content but lacks details on behavioral traits such as error handling (e.g., invalid URLs, authentication needs), rate limits, or what 'content' entails (e.g., raw HTML, parsed text). This leaves significant gaps for an agent.
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 with zero waste—it directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.
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 low complexity (1 parameter, no output schema, no annotations), the description is minimally complete. It covers the basic purpose but lacks details on behavior and output, which are needed for full contextual understanding. It's adequate but has clear gaps.
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?
Schema description coverage is 100%, with the parameter 'url' fully documented in the schema. The description adds no additional meaning beyond implying it's for Scrapbox pages, which the schema example already suggests. 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 action ('Fetch content') and target resource ('from a Scrapbox page by URL'), making the purpose immediately understandable. It doesn't need to differentiate from siblings since none exist, but it could be more specific about what 'content' includes (e.g., text, metadata, structure).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing page content from a Scrapbox URL, but provides no explicit guidance on when to use this tool versus alternatives (e.g., other fetching methods) or any prerequisites. With no sibling tools, the baseline is adequate but unguided.
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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- Evaluate tool definition quality.
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