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analyze_image_with_gemini

Read-only

Analyze local image files or image URLs using Google Gemini Vision when the current model lacks native vision. Requires explicit user consent before sending data to Gemini.

Instructions

Analyze a local image file or image URL using Google Gemini Vision.

PRIVACY RULES:

  1. Use this tool ONLY when the current main model cannot natively understand images.

  2. If the current main model has native vision capability, do NOT use this tool unless the user explicitly asks to use Gemini.

  3. Before calling this tool with confirm_send_to_gemini=true, you MUST ask the user for consent.

  4. The image bytes and prompt will be sent to Google Gemini API.

  5. If image_source is a URL, this MCP downloads the image from your machine first, then sends bytes to Gemini.

  6. If the user has not explicitly agreed, omit confirm_send_to_gemini or set it to false to show a confirmation notice only.

Supported inputs:

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_sourceYesLocal image path or HTTP/HTTPS image URL. Examples: C:/Users/me/Desktop/a.png or https://example.com/a.png
promptNoWhat to analyze. Example: 'Extract all visible text and summarize the screenshot.'
modelNoOverride the Gemini model for this call. Examples: gemini-2.5-flash, gemini-2.5-pro. Defaults to env GEMINI_VISION_MODEL.
confirm_send_to_geminiNoMust be true only after the user explicitly agrees to send this image to Gemini. Defaults to false.
Behavior5/5

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

Annotations indicate readOnlyHint=true and destructiveHint=false. The description adds key behavioral context: image bytes are sent to Google Gemini API, URL images are downloaded first, and consent is required. This goes beyond annotations without contradicting them.

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 verbose, especially the 'PRIVACY RULES' section which repeats consent requirements. While front-loaded with the main purpose, the detailed rules could be condensed. Some sentences could be combined without losing clarity.

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?

The description covers input and behavioral aspects well, but does not explain the output/return format. Since there is no output schema, the agent lacks information on what the tool returns (e.g., text, JSON). This is a significant gap for a tool that produces results.

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

Parameters5/5

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

The input schema has 100% coverage with descriptions for all 4 parameters. The description adds meaningful examples (e.g., image_source paths, prompt text, model overrides) and explains the special behavior of confirm_send_to_gemini. This adds significant value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes images using Gemini Vision, but does not explicitly differentiate from the sibling tool 'analyze_images_batch' (which presumably handles batch processing). The purpose is specific but could be clearer about scope.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use (only when main model lacks vision) and when-not-to-use (main model has vision, unless user requests). It also mandates user consent before calling with confirm_send_to_gemini=true. These guidelines are thorough and actionable.

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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