Skip to main content
Glama
MARUCIE
by MARUCIE

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v2.0.1

  • Disambiguation5/5

    Each tool has a distinct purpose: listing services, retrieving credentials, and making proxy requests. There is no overlap in functionality.

    Naming Consistency5/5

    All three tools follow a consistent verb_noun pattern with snake_case, making them predictable and easy to distinguish.

    Tool Count5/5

    Three tools is well-scoped for a focused credential management server, covering the essential operations without unnecessary bloat.

    Completeness4/5

    The set covers the core workflow of discovering, retrieving, and using credentials. Missing create, update, and delete operations, but these may be out of scope for a vault that manages existing credentials.

  • Average 4.4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 95 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.

  • 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.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

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

    Then . Browse examples.

  • Add related servers to improve discoverability.

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

  • Behavior3/5

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

    With no annotations, the description carries full burden. It discloses the security behavior (credential injection without exposure) but does not mention rate limits, error behavior, or whether the request is read-only or can modify state (depending on method). Sufficient but minimal.

    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 sentences, no wasted words. Front-loaded with the primary action, then adds the critical security benefit. Highly concise and well-structured.

    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?

    Given the tool has 5 parameters (3 required) and no output schema, the description adequately covers the core functionality and security context. It could mention expected response format or error handling, but the key aspects are present.

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

    Parameters3/5

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

    Schema coverage is 100%, so baseline is 3. The description adds no additional parameter meaning beyond what is in the schema; it only reaffirms that credentials are injected automatically, which is already in the headers parameter description.

    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 the action (make authenticated HTTP request), the resource (through Auth Box), and the key benefit (credential injection without exposure). It distinguishes from sibling tools: get_credential retrieves credentials, while this tool uses them for requests.

    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 says 'This is the preferred method for using credentials,' implying the agent should use this tool over alternatives like get_credential when making authenticated requests. However, it does not explicitly contrast with siblings or state when not to use it.

    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 provided, the description carries full burden. It discloses that returned fields are filtered by the agent's access policy and that raw secrets are only returned if policy allows 'read'. This is key behavioral information for a sensitive read operation, but it could mention error behavior (e.g., if service not found or insufficient permissions).

    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, front-loaded sentences. Every sentence adds essential information: purpose and security behavior. No fluff or repetition.

    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 credential retrieval tool, it covers purpose, parameter usage with policy, and security constraints. The absence of an output schema is mitigated by describing what is returned. Could mention response format or example for completeness, but overall adequate.

    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 input schema has 100% description coverage, but the description adds value by explaining how the 'fields' parameter interacts with access policy (only returns permitted fields). This extra context elevates the parameter understanding beyond the bare schema definitions.

    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?

    Clearly states 'Retrieve a credential from the Auth Box vault', specifying a verb and resource. It distinguishes from sibling 'list_available_services' by focusing on actual credential retrieval, and from 'proxy_authenticated_request' which is for making requests, not retrieving stored credentials.

    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?

    Provides clear context on when to use the tool—to retrieve a credential—and includes a critical security caveat about access policy and 'read' action. However, it does not explicitly state when not to use it or compare with alternatives, though the sibling distinction is implicit.

    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 full burden. It discloses the tool returns only names, not secrets, and lists only services with stored credentials. However, it could mention that it is a read-only operation with no side effects, though the listing nature implies safety.

    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 sentences, front-loaded with the action, and no redundant information. Every word contributes value.

    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 tool with no parameters and no output schema, the description is complete: it explains the purpose, the output scope, and a usage scenario. No additional details are needed.

    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 input schema has zero parameters, so schema coverage is 100%. The description adds no parameter info, which is appropriate since none exist. Baseline score of 4 for no parameters.

    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 the tool lists services with stored credentials, distinguishing itself from siblings like get_credential (which returns secrets) and proxy_authenticated_request (which uses credentials). The verb 'List' is specific and the resource is well-defined.

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

    Usage Guidelines5/5

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

    Explicitly states it is 'useful for discovering what credentials are available before making requests', providing clear context for when to use. It also notes it returns 'service names only, no secrets', implicitly guiding the agent to use get_credential for secret retrieval.

    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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

authbox MCP server

Copy to your README.md:

Score Badge

authbox MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/MARUCIE/authbox'

If you have feedback or need assistance with the MCP directory API, please join our Discord server