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image-mcp

image-mcp

by systemmin
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

vision_qa

Ask questions about a local image and get answers from the model based on image content.

Instructions

针对一张本地图片提问，模型根据图片内容回答

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": {
      "path": "<path>",
      "question": "<question>"
    },
    "name": "vision_qa"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes本地图片文件的路径
providerNo视觉 API 后端: anthropic | zhipu | ollama。不传则使用默认 provider
questionYes针对图片提出的问题

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It states the core behavior (answer based on image content) but lacks details on output format, file size limits, supported image types, or whether the operation is read-only. Adequate but not thorough.

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?

Single sentence that is front-loaded with the core action and resource. No wasted words; every part adds value.

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 no output schema and moderate complexity (3 parameters), the description fails to mention what the answer looks like (text, JSON, etc.) or any error handling. It is functional but lacks completeness for a tool with no annotations.

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 of 3 applies. Description does not add extra semantic information beyond what the schema already provides for each parameter; it merely reiterates in a different language.

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?

Description clearly states verb 'ask a question' and resource 'local image', and the action of answering based on content. It effectively distinguishes from sibling tools 'vision_analyze' and 'vision_describe' which imply analysis or description rather than Q&A.

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?

Description implies usage when a user has a specific question about a local image, but provides no explicit guidance on when to use alternatives or when not to use this tool. The context from sibling names is present but not leveraged.

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

Deploy Server

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