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zampou-code

@skynode/mcp

by zampou-code
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TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools are clearly distinct: list_servers provides a high-level overview of all servers, while server_status gives detailed information for a specific server. There is no ambiguity in their purposes.

    Naming Consistency3/5

    Naming is not fully consistent: list_servers follows a verb_noun pattern, while server_status uses a noun_phrase without a verb. Both are readable, but the mixed patterns make the set slightly less predictable.

    Tool Count3/5

    With only two tools, the server is minimal but appropriate for a read-only server information utility. However, it feels thin if broader server management capabilities are expected.

    Completeness4/5

    For a read-only toolset, it covers the essential operations: listing all servers and retrieving detailed status for one. Missing actions like start/stop are out of scope, but the read-only domain is well covered.

  • Average 4.5/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 13 commits in the last 12 weeks
    • No stable releases found
    • 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    With no annotations provided, the description carries the full burden. It discloses read-only nature ('Lecture seule') and enumerates the returned fields (name, IP, state, ID), offering useful behavioral context beyond the empty schema.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is compact—two sentences—with the main purpose front-loaded and no superfluous content. Every sentence contributes value.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple list operation with no parameters and no output schema, the description provides essential information: what is returned, that it is read-only, and when to use it. It adequately covers the tool's context given its simplicity.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The tool accepts zero parameters, so there is no parameter semantics to convey. The baseline for no parameters is 4, and the description correctly omits any parameter details.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states it lists SkyNode VPS servers with their name, IP, state, and ID, using the specific verb 'list' and resource 'servers (VPS) of the SkyNode account'. It also differentiates from the sibling tool 'server_status' by indicating it should be called first to know which machine to work on.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly instructs to call this tool first to determine the machine to work on, providing clear usage context. It does not explicitly mention exclusions or alternatives, but the sequencing guidance is sufficient for typical workflows.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description carries the burden of disclosing behavior. It explicitly states 'Lecture seule' (read-only) and enumerates what information is returned. It does not discuss errors or permissions, but for a read-only detail endpoint this is sufficient.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two concise sentences, front-loaded with the tool's purpose and output fields. Every word earns its place with no redundancy.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple single-parameter read-only tool with no output schema, the description fully covers what the tool does, what it returns, and how to obtain the required ID. It is complete for an agent to invoke correctly.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, so the schema already defines server_id. The description adds value by telling the agent that the ID comes from list_servers, which is genuinely useful contextual information beyond the schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Uses the specific verb 'Détaille' with a clear resource ('un serveur') and lists concrete attributes (état, adresses IP, système, etc.). It clearly distinguishes itself from list_servers by focusing on a single server's detailed status.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly tells the agent to obtain the identifier via list_servers, establishing a clear usage flow. It does not mention when not to use it, but for a simple detail lookup the context is clear.

    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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  • 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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