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chrishayuk

chuk-mcp-s3-bucket-manager

by chrishayuk
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.1

  • Disambiguation5/5

    The three tools—list, create, delete—are clearly distinct actions on S3 buckets with no overlap. An agent can easily select the right tool based on the desired operation.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with underscores (list_buckets, create_bucket, delete_bucket), making the set predictable and easy to navigate.

    Tool Count5/5

    With only three tools, the set is minimal but perfectly scoped for a basic S3 bucket manager. Each tool covers an essential operation without redundancy.

    Completeness3/5

    The set covers list, create, and delete, but lacks an update operation and a way to fetch details of a specific bucket. While list_buckets can serve as a read, the absence of update leaves a notable gap for a 'manager'.

  • Average 3.4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 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

  • 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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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 exist to declare safety or mutation, and the description adds no behavioral context such as idempotency, permission needs, failure modes, or side effects. 'Create' implies mutation but nothing more.

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

    Conciseness4/5

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

    The description is a single, front-loaded sentence with no waste. It is concise, though it could have used the space to add useful detail without becoming verbose.

    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?

    With no output schema or annotations, the description should at least mention what happens on success or important constraints. It provides none, making it insufficient for an agent to fully understand invocation outcomes.

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

    Parameters2/5

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

    The schema has 0% description coverage, and the description does not explain bucket_name semantics (e.g., naming rules, uniqueness, format). It merely repeats the action without adding value beyond the raw parameter name.

    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 uses the specific verb 'Create' with the resource 'S3 bucket', clearly identifying the tool's action. It distinguishes from siblings list_buckets and delete_bucket by the action verb.

    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?

    There is no guidance on when to use this tool versus alternatives. No prerequisites, context, or exclusions are provided; the description only states the basic action.

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

  • Behavior2/5

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

    No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the action ('delete'), making the destructive nature implicit but failing to disclose the 'force' parameter's effect (e.g., deleting non-empty buckets) or irreversibility.

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

    Conciseness3/5

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

    The description is a single concise sentence, but it under-specifies an operation that has a nontrivial parameter ('force'). It is not verbose, but the extreme brevity limits its usefulness.

    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?

    Given the lack of annotations, output schema, and schema descriptions, the tool description is insufficient. It doesn't mention error conditions, whether force is required for non-empty buckets, or any safety implications, making it incomplete for a destructive operation.

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

    Parameters1/5

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

    Schema coverage is 0%, and the description does not explain any parameters. 'bucket_name' is self-evident from its name, but 'force' is a boolean with no explanation of its meaning or when to set it, leaving the agent without critical 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 the tool's purpose with a specific verb ('Delete') and resource ('an S3 bucket'), distinguishing it from sibling tools list_buckets and create_bucket.

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

    Usage Guidelines3/5

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

    Usage is implied (use when you want to remove an S3 bucket) but no explicit context or alternatives are provided. It doesn't mention prerequisites like the bucket existing or being empty.

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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. The verb 'list' implies a read-only operation, but the description does not explicitly state that it has no side effects or mention any permissions or rate limits. For a simple list operation, this is acceptable but could be more explicit.

    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, brief sentence that fully conveys the tool's purpose. Every word earns its place with no redundancy or unnecessary detail.

    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?

    The tool is extremely simple with no parameters and no output schema. The description fully covers the tool's behavior and scope. There is no missing information that would hinder an agent from using it 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?

    The tool has zero parameters, so the schema is empty and this dimension is not applicable. Per the rubric, a baseline of 4 is appropriate when there are no parameters to describe.

    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 'List all S3 buckets' uses a specific verb ('list') and clearly identifies the resource ('S3 buckets') and scope ('all'). This clearly differentiates it from the sibling tools create_bucket and delete_bucket.

    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 context is clear: the tool lists buckets, which is distinct from creating or deleting. There are no exclusions or alternative tools mentioned, but the name and description make the usage obvious given the sibling tool names.

    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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