Best for
- Developers looking to quickly integrate AI vision capabilities, especially within Google's AI ecosystem.
- Design teams needing UI/UX compliance and accessibility audits.
- Workflows requiring automated image and video analysis.
A
AI Vision MCP Server
Community
AI-powered image and video analysis MCP server using Gemini and Vertex AI
GitHub source repository ↗
64FMRS · C
The AI Vision MCP server provides comprehensive image and video analysis tools with multiple providers and file sources, designed for the MCP ecosystem. Its strengths include flexibility, validation, and error handling, but it requires external API keys and attention to data privacy and cost.
The AI Vision MCP server is a Model Context Protocol (MCP) server that provides AI-powered image and video analysis using Google Gemini and Vertex AI models. It supports multiple file sources (URLs, local files, base64), offers tools for image analysis, image comparison, object detection with bounding boxes, UI/UX design auditing, and video analysis. The server features dual provider support (Google and Vertex AI), built-in Google Cloud Storage integration, Zod-based validation, and robust error handling with retries and circuit breakers.
Tools
analyze_image
Analyzes an image and returns a detailed description, with modes for general, palette, hierarchy, and components.
compare_images
Compares multiple images (2-4) and returns a detailed comparison analysis.
detect_objects_in_image
Detects objects in an image and generates annotated images with bounding boxes, returning coordinates and a summary.
audit_design
Audits UI/UX design compliance with pixel analysis, WCAG contrast checks, and AI critique.
analyze_video
Analyzes a video and returns a detailed description, supporting YouTube URLs, GCS URIs, or local file paths.
Setup
- Install Node.js 18+ and npm.
- Configure environment variables: either for Google AI Studio (set IMAGE_PROVIDER=google, VIDEO_PROVIDER=google, GEMINI_API_KEY) or Vertex AI (set IMAGE_PROVIDER=vertex_ai, VIDEO_PROVIDER=vertex_ai, VERTEX_CLIENT_EMAIL, VERTEX_PRIVATE_KEY, VERTEX_PROJECT_ID, GCS_BUCKET_NAME).
- Add the server to your MCP client: For Claude Desktop, add a configuration like { "mcpServers": { "ai-vision-mcp": { "command": "npx", "args": ["ai-vision-mcp"], "env": { ... } } } } to your config file. For Claude Code, use
claude mcp add ai-vision-mcp -e ... -- npx ai-vision-mcp. For Cursor, add to ~/.cursor/mcp.json. For Cline, add to cline_mcp_settings.json. - Increase MCP client timeout to >1 minute and tool execution timeout to ~5 minutes.
Fit and risk
Not for
- Not suitable for scenarios requiring offline or on-premise AI models.
- Not for integrations with non-Google cloud resources (e.g., AWS).
- May not be ideal for complex video editing or real-time streaming needs.
Required permissions
- Requires access to Google AI Studio API or Vertex AI API credentials.
- For local file analysis, needs read access to the local filesystem.
- If using Vertex AI, needs access to a Google Cloud Storage bucket.
- For video analysis, needs access to YouTube or local video files.
Risks and side effects
- API key leakage: environment variables contain sensitive credentials; store them securely.
- Data privacy: images/videos sent to Google Cloud may contain sensitive information; ensure compliance.
- Cost: API usage may incur costs based on volume.
- Potential timeout or transport errors if not configured properly.
Troubleshooting
- If 'Transport closed' appears, ensure no logs are written to stdout; use console.error instead.
- Check that the imagescript dependency loads correctly: run npm run doctor or npm run check:imagescript.
- Verify environment variables are set correctly, especially API keys and provider selection.
- Increase MCP client timeout settings to avoid timeouts during long analyses.
Use cases
Describe image content for accessibility or content moderation.
Compare design mockups or screenshots.
Automate object detection for inventory or quality control.
Audit UI designs for accessibility compliance (WCAG).
Analyze video content for summaries or insights.
Supported clients
Claude DesktopFull support
Claude CodeFull support
CursorFull support
ClineFull support