gemini-image-mcp

Analyze image with Gemini

analyze_image

Analyze local image files or URLs with Google's Gemini vision models to extract text descriptions or answer questions about screenshots, diagrams, and UI states without loading raw image bytes.

Instructions

Analyze a local image file (or image URL) with Google's Gemini vision models and return a text answer. Use this to read screenshots, diagrams, charts, or UI states without loading raw image bytes into the calling agent's context.

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	Description
`image`	Yes	Absolute path to a local image file, or an http(s) URL.
`prompt`	No	Question/instruction about the image. Defaults to a detailed description.
`model`	No	Override the Gemini model (e.g. gemini-pro-latest for harder visual reasoning).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 14, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions that the tool returns a 'text answer', but does not elaborate on limitations (e.g., file size, format support), security considerations, or whether the image is sent to an external service.

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 sentences that efficiently convey the tool's purpose and usage context. No unnecessary words.

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

Completeness4/5

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

Given the lack of annotations and output schema, the description provides a solid overview of the tool's purpose and usage. However, it could be more complete by mentioning the return format, authentication requirements, or any limitations.

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 description coverage is 100%, so the schema already documents all parameters. The tool description does not add additional meaning beyond the schema, making it adequate but not outstanding.

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 verb 'analyze', the resource ('local image file or image URL'), and the specific use cases ('screenshots, diagrams, charts, or UI states'), making the tool's purpose unambiguous.

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 suggests when to use the tool ('read screenshots, diagrams, charts, or UI states') and highlights a key benefit ('without loading raw image bytes'). However, it does not mention when not to use it or provide alternative tools, so it's not a 5.

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

Deploy Server

Other Tools

analyze_imageA