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sergei-tofu-fedorov

Mongo MCP Server

by sergei-tofu-fedorov
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JavaScript
Hybrid

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 possibility of ambiguity or overlap in purpose. The tool 'check_connection' has a single, clear function, making it impossible for an agent to confuse it with any other tool.

    Naming Consistency5/5

    The single tool name follows a consistent verb_noun pattern ('check_connection'), and with only one tool, there is no inconsistency in naming conventions. The naming is straightforward and predictable.

    Tool Count2/5

    A single tool is too few for a MongoDB server, which typically requires CRUD operations, querying, indexing, and other database management tasks. This minimal set severely limits the server's utility and scope, indicating a significant mismatch with the expected domain coverage.

    Completeness1/5

    The tool set is severely incomplete for a MongoDB server. It lacks essential operations like insert, find, update, delete, or any other database interactions, leaving major gaps that will cause agent failures in performing typical database tasks. The single tool only handles connection checking, which is insufficient for the stated purpose.

  • Average 3.2/5 across 1 of 1 tools scored.

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

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  • 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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. While it implies a read-only, non-destructive operation (checking connection status), it fails to specify what 'active and healthy' entails (e.g., latency thresholds, authentication status), the response format, or any side effects like logging. This leaves significant gaps in understanding the tool's behavior.

    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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is front-loaded with the core action and resource, making it easy to parse and understand immediately.

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

    Completeness3/5

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

    Given the tool's simplicity (no parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits, response format, or usage context. For a diagnostic tool, more information on what constitutes 'healthy' would enhance completeness, but the current description meets the basic requirement.

    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 has zero parameters, and schema description coverage is 100%, meaning there are no parameters to document. The description appropriately does not mention parameters, aligning with the schema. A baseline of 4 is applied since no parameter information is needed, though it doesn't add value beyond the schema's indication of no parameters.

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

    Purpose4/5

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

    The description clearly states the tool's purpose: 'Check if MongoDB connection is active and healthy.' It specifies the verb ('check') and the resource ('MongoDB connection'), making the intent unambiguous. However, with no sibling tools mentioned, there's no opportunity to distinguish from alternatives, preventing a perfect score.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives or in what context it should be invoked. It lacks any mention of prerequisites, timing, or scenarios where this check is appropriate, leaving the agent without operational context.

    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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  • Evaluate tool definition quality.

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