mcp-ovh-api
Server Quality Checklist
Latest release: v0.2.1
- Disambiguation5/5
With only one tool, there is no possibility of confusion between tools. The single tool's purpose is clearly defined and distinct.
Naming Consistency5/5The lone tool name follows a clean snake_case verb_noun pattern. With only one tool, there are no inconsistencies to evaluate.
Tool Count1/5A single status-check tool is drastically insufficient for a server named 'mcp-ovh-api' covering the OVH cloud API. The count represents an extreme mismatch between the server's implied scope and its actual surface.
Completeness1/5The server exposes no operations beyond an authentication status check. Any actual OVH API functionality is absent, making the tool surface severely incomplete for the stated domain.
Average 4.7/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 18 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already marks this as safe, and the description adds useful behavioral context by stating it reports credential validity, auth method, endpoint, project/region, and write status. It also says missing credentials explain absent tools, which clarifies what the status check means. It doesn't explicitly describe network/read behavior, but the annotation plus 'report' wording make the safety profile clear.
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?
Two sentences carry a full purpose statement, a detailed list of outputs, and a usage rule. The key diagnostic trigger ('Call this first when a tool you expected is not listed') is placed second and is memorable. No word is wasted.
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?
For a tool with no parameters, no siblings, and no output schema, the description is self-sufficient: it tells the agent what information the tool produces and when to invoke it. The only omitted detail, the exact configuration values to set, is precisely what the tool's output is described as providing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so there is nothing to document beyond the empty schema. The description still clarifies the kind of status data returned, which is consistent with a no-input diagnostic tool. Baseline 4 is appropriate for a 0-parameter definition.
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 opens with a specific verb and resource: 'Report whether this server has working OVHcloud credentials,' then enumerates exactly what is reported (auth method, endpoint, default project/region, write enablement). This is unambiguous and fully distinguishes the tool from any conceivable alternative, even though no siblings are listed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit call heuristic: 'Call this first when a tool you expected is not listed,' and even frames the diagnostic interpretation ('an absent tool here means missing configuration, not a bug'). This tells an agent not only when to run it but how to interpret the result.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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.
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