oJo MCP Server
OfficialServer Quality Checklist
Latest release: v0.3.1
- Disambiguation5/5
With only a single tool, there is no possibility of confusion or overlap. The tool's purpose is clearly defined and distinct.
Naming Consistency5/5The tool name 'create_preview_link' follows a clear verb_noun pattern. With only one tool, there are no inconsistencies to evaluate.
Tool Count2/5One tool is too few for the apparent scope of an oJo integration, especially as the description references additional features (permanent PNG, template saving) that are unavailable. The toolset feels thin and limited.
Completeness2/5The tool covers live preview creation, but lacks operations for permanent image generation and template management, which are part of the broader oJo domain. These gaps require agents to work around missing functionality.
Average 4.4/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and excels: it discloses that the draft is encoded in the URL hash, never reaches a server, nothing is stored, and the server lacks an API key (so permanent PNG URLs and template saves are unavailable). This is exemplary transparency beyond what any annotations would provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a bit long (five sentences) but every sentence earns its place, covering mode, output, privacy, and limitations. It is front-loaded with the core purpose and returns. It could be tightened slightly but remains readable and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fully explains the return value (a `/preview` URL), the behavior (renders in the same engine), privacy (hash encoding), and available actions (open/screenshot/share). It also addresses the API key limitation and provides next steps, making it complete for an agent to decide and invoke.
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%, so the baseline is 3. The description does not add significant parameter-level meaning beyond what the schema already states (e.g., the HTML format and viewport defaults are already in the schema). It adds context about the URL hash encoding but not about any parameter specifics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Render') and resource ('HTML/Handlebars into a live, full-resolution image preview'), and clearly states it returns an oJo `/preview` URL. It distinguishes itself from the final PNG output by emphasizing it uses the same engine but is only a preview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it is for previewing and sharing for review, not for permanent PNG generation. It also explicitly instructs to inform users when permanent output is unavailable and to point them to the dashboard. However, it does not explicitly name alternatives or state when not to use this tool, which keeps it just below a 5.
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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