mcp-vision-server

analyze_image

Analyze images to extract text, answer visual questions, and restore UI mockups. Supports screenshots, photos, and custom prompts.

Instructions

Analyze or understand an image.

Use this tool when an MCP client needs image understanding, screenshot analysis, OCR-like text recognition, visual Q&A, or UI restoration.

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": "analyze_image"
  }
}

Input Schema

Name	Required	Default
`image`	Yes
`model`	No
`prompt`	No	请详细描述这张图片。
`api_key`	No
`base_url`	No
`provider`	No
`image_type`	No	auto
`max_tokens`	No
`temperature`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jul 9, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It states the tool can 'analyze' an image but does not reveal that it likely calls an external API (implied by parameters like api_key, base_url, provider), nor does it describe side effects, idempotency, or return behavior beyond the output schema.

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 very concise: two sentences summarizing purpose and use cases. It is front-loaded and wastes no words. However, it could be slightly more structured (e.g., separate parameter notes) to improve readability.

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 tool's complexity (9 parameters, output schema exists, sibling tool), the description is incomplete. It lacks parameter guidance, input/output format details, and prerequisites (e.g., API key requirements). The output schema exists but is not referenced. The description should provide more context for accurate invocation.

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 description coverage is 0%, yet the description provides no explanation for any of the 9 parameters (image, model, prompt, api_key, base_url, provider, image_type, max_tokens, temperature). It fails to add meaning beyond the schema, leaving the agent to guess parameter usage.

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: 'Analyze or understand an image.' It provides specific use cases (image understanding, screenshot analysis, OCR, visual Q&A, UI restoration) which distinguishes it from the sibling tool 'list_providers' and gives a precise verb-resource relationship.

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 explicitly lists when to use the tool (e.g., when image understanding or OCR is needed) and implies a specific context. However, it does not mention when not to use it or suggest alternative tools, which would improve guidance.

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

Deploy Server