A
licenseA
qualityC
maintenanceEnables Claude Code to describe images and extract text using Kimi/Moonshot vision API. Supports local image files with customizable prompts.
2
MIT
mcp-vision
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-vision What's in this image? /Users/me/Desktop/sunset.png"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-vision
GitHub: lbyxunxunnini/mcp-vision · License: MIT · 当前版本：v0.1.0
MCP Server for image recognition, powered by Kimi K2.5 (Infini-AI).
Features
recognize_image- Recognize and describe images using multimodal AI
Related MCP server: Image Parse MCP
Prerequisites
Node.js >= 18
An Infini-AI API key (https://cloud.infini-ai.com)
Installation
# 1. Extract the archive
tar -xzf mcp-vision.tar.gz
cd mcp-vision
# 2. Install dependencies and build
npm install && npm run buildClaude Code Configuration
Add the following to your Claude Code settings (~/.claude/settings.json or project .claude/settings.json):
{
"mcpServers": {
"vision": {
"command": "node",
"args": ["/path/to/mcp-vision/dist/index.js"],
"env": {
"INFINI_API_KEY": "your-api-key-here"
}
}
}
}Replace /path/to/mcp-vision with the actual path where you extracted the project.
Usage
Once configured, the mcp__vision__recognize_image tool is available in Claude Code.
Parameters
Parameter | Type | Required | Description |
| string | Yes | Absolute path to the local image file |
| string | No | Custom instruction, e.g. "extract all text", "describe the UI layout" |
Supported Formats
PNG, JPG, JPEG, GIF, WebP, BMP
Example
请识别这张图片: /Users/me/Desktop/screenshot.pngClaude Code will automatically call the MCP tool to process the image.
Environment Variables
Variable | Description |
| Required. Your Infini-AI API key |
Available Tools
1 toolrecognize_imageC
Recognize and describe an image using a multimodal model (Kimi K2.5). Returns a text description of the image content.
Inputs: image_path (required), prompt.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
B3.1/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool's purpose is clearly defined.
Naming Consistency5/5
The single tool uses a clear verb_noun pattern (recognize_image) with snake_case, which is consistent and readable. No inconsistency exists.
Tool Count2/5
A single tool is too few for a server named 'mcp-vision,' which implies a broader scope. The tool count falls into the 'too few' category, limiting functionality.
Completeness2/5
The server only offers image description, lacking other common vision tasks (e.g., object detection, OCR). This is a significant gap for a general vision server.
Maintenance
ActivityInactive
ResponsivenessNo recent community issues
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Search bilingual image prompts, upload reference images, and generate and download images from your AI agent. OAuth sign-in; image generation uses paid subscription credits. Setup: https://framepond.com/en/agent?utm_source=agent_directory&utm_campaign=agent_launch
AI image + video generation for agents: --flag prompt DSL, async generate/poll, x402 pay-per-use.
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