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rlaksana

mcp-cli-gemini

by rlaksana
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no risk of confusing it with another. The tool's purpose is clearly stated, so an agent can unambiguously select it.

    Naming Consistency5/5

    The single tool name 'gemini' is simple, matches the server name, and follows a consistent pattern. With only one name, there are no inconsistencies to penalize.

    Tool Count2/5

    Exposing only one tool is too few for the apparent scope, as it tries to cover queries, interactive mode, and extension management all in one. This forces the agent to rely on a single catch-all, which is impractical and not a well-structured tool set.

    Completeness2/5

    The single tool is a thin wrapper around the entire CLI, providing no first-class operations for distinct tasks. Agents must manually construct CLI commands, which is error-prone and represents a shallow API surface compared to a more complete, structured set.

  • Average 3.6/5 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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  • 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

  • Behavior2/5

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

    With no annotations provided, the description must disclose behavioral traits, but it only lists capabilities without addressing side effects, safety, or operational nuances. The schema hints at behaviors like yolo mode (auto-approve), sandbox, and interactive mode, but the description itself does not mention these or any potential risks, making it inadequate for a command-execution tool.

    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 exceptionally concise, consisting of two short sentences that immediately state the core action and enumerate supported modes. There is no redundancy or fluff, and the most critical information is front-loaded.

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

    Completeness2/5

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

    Despite having six parameters and no output schema, the description provides only a high-level summary of capabilities. It does not explain how the modes interrelate, what the tool returns, or any execution details, leaving the agent to rely entirely on the schema for context. This is insufficient for a tool of this complexity.

    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 description coverage is 100%, so each parameter is already well-defined in the input schema. The tool description adds no additional meaning beyond the schema, which is acceptable per the baseline; it neither enhances nor detracts from parameter understanding.

    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 'Execute Gemini CLI commands' with a specific verb and resource, and further enumerates the tool's main capabilities: queries, interactive mode, and extension management. This fully clarifies the tool's purpose and differentiates it from potential siblings (though none are present).

    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 provides clear context on the tool's intended use cases by listing the three supported modes (queries, interactive mode, extension management). While it does not explicitly state when not to use this tool or name alternatives, the absence of siblings and the explicit enumeration offer sufficient guidance for an agent to determine applicability.

    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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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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