Borrowing it
Nothing to install: this file belongs to Desmond-Labs/ai-image-analysis-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Desmond-Labs/ai-image-analysis-mcp/main/CLAUDE.mdgit clone --depth 1 https://github.com/Desmond-Labs/ai-image-analysis-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/desmond-labs/ai-image-analysis-mcp/claude-md)<a href="https://agentmods.dev/instructions/desmond-labs/ai-image-analysis-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/desmond-labs/ai-image-analysis-mcp/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/desmond-labs/ai-image-analysis-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/desmond-labs/ai-image-analysis-mcp/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.06652 | $0.06652 |
| Opus 5 | $0.03326 | $0.03326 |
| Sonnet 5 | $0.01330 | $0.01330 |
| Haiku 4.5 | $0.00665 | $0.00665 |
Grade C, and why
ai-image-analysis-mcp CLAUDE.md scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Cloud metadata endpointhighServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
'169.254.169.254' // AWS metadata service Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "https://your-project.supabase.co/functions/v1/ai-image-analysis-mcp" \ This is a copy
100% identical to ai-image-analysis-mcp CLAUDE.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 794 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Image Analysis MCP v2.0
AI-Powered Image Analysis with Google Gemini 2.0 Flash
Model Context Protocol server with serverless deployment and multi-client access
🚀 Mission Overview - Production Ready ✅
The AI Image Analysis MCP v2.0 represents a production-ready implementation of AI-powered visual intelligence processing. This battle-tested server provides comprehensive image analysis using Google Gemini 2.0 Flash with complete serverless deployment, advanced security features, modular architecture, and multiple client access methods.
Core Value Proposition: Transform any image into rich, intelligent analysis data through secure, scalable AI processing, with production-ready deployment options, enterprise-grade reliability, and flexible integration capabilities.
🎯 Production Status Overview
- ✅ Real Gemini 2.0 Integration: Complete implementation (no mocks)
- ✅ Serverless Deployment: Full Supabase Edge Function ready
- ✅ Multiple Client Access: HTTP, MCP, Web, and cURL interfaces
- ✅ Modular Architecture: Clean separation of concerns and maintainability
- ✅ Enterprise Security: Comprehensive validation and monitoring
- ✅ Performance Optimized: Sub-5-second response times at scale
- ✅ Battle Tested: Production-ready error handling and recovery
🎯 Key Features
🧠 Production AI Analysis Engine
- Google Gemini 2.0 Flash: Real API integration with latest multimodal AI capabilities
- Automatic Type Detection: Intelligent classification between lifestyle and product images
- Dynamic Analysis Adaptation: Analysis depth automatically adjusted based on image content
- Contextual Intelligence: Advanced understanding of cultural, social, and commercial contexts
- Quality Assessment: AI-powered evaluation of commercial viability and professional quality
- Real-time Processing: Optimized for production speed with <5-second response times
📊 Comprehensive Analysis Intelligence
- Lifestyle Analysis: Scene understanding, human behavior, environmental context, and narrative intelligence
- Product Analysis: Technical specifications, design attributes, commercial potential, and market positioning
- Marketing Intelligence: Target demographics, brand alignment, emotional hooks, and commercial applications
- Cultural Analysis: Social significance, lifestyle values, aspirational elements, and cultural context
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 794 lines · 6,652 tokens per session scan C 62e22689011f
ai-image-analysis-mcp CLAUDE.md is an instructions file published in the GitHub repository Desmond-Labs/ai-image-analysis-mcp (0 stars, last pushed 1y ago), licensed MIT. It adds 6,652 tokens to every session, about $0.0333 per session on Opus 5. A static security scan graded it C with 2 findings (cloud metadata endpoint, makes network calls). It is 100% identical to ai-image-analysis-mcp CLAUDE.md, differing in 0 lines, and is treated as a copy.
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