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docker-hub-mcp

docker-hub-mcp

by GeniusTechnoMystic
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_image_stats

Retrieve Docker Hub image metadata including pull count, stars, description, official status, and last update. Simplifies image name handling by auto-prefixing 'library/'.

Instructions

Fetch metadata for a single Docker Hub image. Accepts both 'library/nginx' and 'nginx' (auto-prepends 'library/') formats. Returns pulls, stars, description, official/verified status, last updated.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "image": "<image>"
    },
    "name": "get_image_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYesDocker image name: 'nginx', 'python', 'grafana/grafana', etc.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and discloses useful behavior: it accepts both 'library/nginx' and 'nginx' formats with auto-prepending, and lists return fields. However, it does not explicitly mention read-only status or error conditions, though these are minor for a metadata fetch.

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-load the purpose and add only essential details (format handling and return fields). No waste or 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 tool with one parameter and no output schema, the description fully covers input formats and return fields, making it complete for the agent to use 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 input schema already documents the parameter with examples, but the description adds the key behavior of auto-prepending 'library/' and the two accepted formats, providing meaningful semantic context 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?

Clearly states it fetches metadata for a single Docker Hub image, with a specific verb and resource. It distinguishes from siblings like batch_image_stats by emphasizing 'single' and listing specific return fields.

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 (single image metadata) and implies batch use for multiple images, but does not explicitly name alternatives or state when not to use this tool. It is effective but lacks explicit exclusion guidance.

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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