Which integrations are available for this server?

Provides vision AI capabilities (image analysis, OCR, UI-to-code, error diagnosis, etc.) via OpenAI's GPT-4o model.

How do I use Vison-MCP?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Vison-MCP diagnose this error screenshot and suggest fixes" 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.

Vison-MCP

by Lin-zhibo

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

Vison-MCP

MCP server for vision AI — screenshots to code, OCR, error diagnosis, and image analysis via OpenAI-compatible APIs.

Supported Tools

Tool	Description
`image_analysis`	General visual understanding — describe any image in detail
`extract_text_from_screenshot`	OCR optimized for terminals, code, documents, and general content
`ui_to_artifact`	Convert UI screenshots into code, prompts, specs, or descriptions
`diagnose_error_screenshot`	Analyze error screenshots and propose actionable fixes
`understand_technical_diagram`	Interpret architecture diagrams, flowcharts, UML, ER, and system diagrams
`analyze_data_visualization`	Read charts and dashboards to surface insights, trends, and anomalies
`ui_diff_check`	Compare two UI screenshots to flag visual differences and implementation drift
`video_analysis`	Inspect videos (MP4/MOV/M4V) — scene detection, event analysis, content summarization

Related MCP server: vision-mcp

Installation

git clone https://github.com/Lin-zhibo/Vison-MCP.git
cd Vison-MCP
npm install
npm run build

Configuration

Set the following environment variables:

Variable	Required	Default	Description
`VISIONAI_API_KEY`	Yes	—	API authentication key
`VISIONAI_BASE_URL`	Yes	—	OpenAI-compatible API endpoint
`VISIONAI_MODEL_NAME`	No	`gpt-4o`	Vision model to use

Usage

With Claude Code

Add to your .claude/settings.json or claude_desktop_config.json:

{
  "mcpServers": {
    "vison-mcp": {
      "command": "node",
      "args": ["/path/to/Vison-MCP/dist/index.js"],
      "env": {
        "VISIONAI_API_KEY": "your-api-key",
        "VISIONAI_BASE_URL": "https://api.openai.com/v1",
        "VISIONAI_MODEL_NAME": "gpt-4o"
      }
    }
  }
}

Local Development

# Copy environment template
cp .env.example .env
# Edit .env with your API credentials

# Build and run
npm run build
npm start

Requirements

Node.js >= 18.0.0
An OpenAI-compatible vision API endpoint (GPT-4o, Claude Vision, or compatible)

License

MIT

Available Tools

8 tools

analyze_data_visualizationA

Read charts, dashboards, and statistical visualizations to surface insights, trends, patterns, and anomalies with actionable recommendations.

Inputs: imageUrl (required), analysisFocus.

diagnose_error_screenshotA

Analyze error screenshots (build errors, runtime errors, stack traces) and propose actionable fixes with root cause analysis.

Inputs: imageUrl (required), context.

extract_text_from_screenshotA

Extract text from screenshots. Optimized for terminals, code editors, documents, and general content. Returns extracted text preserving original structure.

Inputs: imageUrl (required), context.

image_analysisB

Analyze any image with a general vision model. Returns a detailed description of the image content, key elements, text, colors, layout, and context clues.

Inputs: imageUrl (required), prompt.

ui_diff_checkA

Compare two UI screenshots — design vs implementation — to identify visual differences, layout drift, style inconsistencies, missing elements, and typography discrepancies.

Inputs: expectedUrl (required), actualUrl (required), prompt.

ui_to_artifactA

Convert UI screenshots into structured deliverables: production-ready code, image-generation prompts, technical specifications, or detailed descriptions.

Inputs: imageUrl (required), outputType.

understand_technical_diagramA

Interpret architecture diagrams, flowcharts, UML, ER, sequence, and system topology diagrams. Returns structured analysis of components, relationships, design patterns, and improvement suggestions.

Inputs: imageUrl (required), diagramType.

video_analysisA

Inspect videos (local files ≤8MB, remote URLs) to describe scenes, detect events, and answer questions about visual moments. Supports MP4, MOV, M4V.

Inputs: videoUrl (required), prompt, maxFrames, fps.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.7/5.0

Scored 2026-06-23 04:20 across 8 tools

Disambiguation5/5

Each tool has a distinct purpose: analyzing data visualizations, diagnosing error screenshots, extracting text, general image analysis, UI diff checking, UI-to-artifact conversion, technical diagram interpretation, and video analysis. No two tools overlap in function.

Naming Consistency3/5

Names use mixed conventions: some follow verb_noun (e.g., analyze_data_visualization, diagnose_error_screenshot), others are noun_noun or use abbreviations (e.g., image_analysis, ui_diff_check, ui_to_artifact). This inconsistency may cause confusion.

Tool Count4/5

With 8 tools, the server covers a broad range of vision tasks without being overwhelming. The count is slightly on the lower side but still well-scoped for a vision-focused MCP.

Completeness4/5

The tool set covers major vision domains: data visualization, error diagnosis, text extraction, general analysis, UI comparison, code generation, technical diagrams, and video. Minor gaps like object detection or facial recognition are acceptable for a general-purpose server.

Maintenance

ActivityInactive

ResponsivenessNo recent community issues

Resources

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Vison-MCP

Supported Tools

Installation

Configuration

Usage

With Claude Code

Local Development

Requirements

License

Available Tools

Tool Schema Changelog

TDQS

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

pic-id-mcp

vision-mcp

vision-mcp

ocular