{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-mcpcnimage-ai-generation-mcp","slug":"npm-mcpcnimage-ai-generation-mcp","name":"@mcpcn/image-ai-generation-mcp","type":"mcp","url":"https://www.npmjs.com/package/@mcpcn/image-ai-generation-mcp","page_url":"https://unfragile.ai/npm-mcpcnimage-ai-generation-mcp","categories":["mcp-servers"],"tags":["mcp","image-generation","ai","nano-banana-pro","kie-ai"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-mcpcnimage-ai-generation-mcp__cap_0","uri":"capability://image.visual.mcp.native.image.generation.with.nano.banana.pro.backend","name":"mcp-native image generation with nano banana pro backend","description":"Exposes image generation as an MCP tool that integrates with the Nano Banana Pro API, allowing Claude and other MCP-compatible clients to invoke image generation through standardized tool-calling protocols. The implementation wraps the Nano Banana Pro REST API endpoints as MCP resources, handling authentication via API keys and marshaling prompt text into generation requests with configurable parameters like model selection, dimensions, and inference steps.","intents":["I want Claude to generate images directly without leaving the conversation or switching tools","I need to build an agent that can create images as part of a multi-step workflow","I want to expose image generation capabilities to any MCP-compatible client without custom integration code"],"best_for":["AI application developers building multi-modal agents with Claude","Teams standardizing on MCP for tool orchestration across LLM applications","Developers prototyping image-generation workflows in Claude conversations"],"limitations":["Dependent on Nano Banana Pro API availability and rate limits — no local fallback or caching layer","No built-in retry logic or exponential backoff for failed generation requests","Synchronous request-response model only — no support for long-polling or webhook callbacks for async generation","No image format negotiation — output format determined entirely by Nano Banana Pro API defaults"],"requires":["Node.js 16+ (MCP SDK requirement)","Valid Nano Banana Pro API key with image generation quota","MCP-compatible client (Claude Desktop, custom MCP host, or compatible IDE)","@mcpcn/image-ai-generation-mcp package installed via npm"],"input_types":["text (natural language image prompt)","optional structured parameters (model name, dimensions, steps)"],"output_types":["image (PNG, JPEG, or WebP depending on Nano Banana Pro response)","metadata (generation timestamp, model used, inference duration)"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcpcnimage-ai-generation-mcp__cap_1","uri":"capability://image.visual.prompt.to.image.generation.with.configurable.model.selection","name":"prompt-to-image generation with configurable model selection","description":"Accepts natural language image prompts and translates them into Nano Banana Pro API requests, with support for selecting specific generative models and tuning inference parameters like step count and output dimensions. The capability maps user-friendly parameter names to Nano Banana Pro's API schema, handling type coercion and validation before transmission.","intents":["I want to generate an image from a text description without learning Nano Banana Pro's API details","I need to switch between different image generation models (e.g., Stable Diffusion variants) for different use cases","I want to control generation quality and speed by adjusting inference steps and resolution"],"best_for":["Content creators using Claude to brainstorm and generate visual assets","Developers building image-heavy applications (e-commerce, design tools, marketing platforms)","Non-technical users who want to generate images through natural conversation"],"limitations":["No prompt optimization or enhancement — raw user prompts sent directly to Nano Banana Pro without semantic improvement","Limited model selection — only models available through Nano Banana Pro's current API offerings","No image-to-image or inpainting capabilities — text-to-image only","Generation latency depends entirely on Nano Banana Pro backend performance (typically 10-60 seconds per image)"],"requires":["Valid Nano Banana Pro API key with sufficient image generation credits","Text prompt (minimum ~10 characters for meaningful generation)","Optional: model name parameter (defaults to Nano Banana Pro's default model if not specified)"],"input_types":["text (image prompt/description)","string (model identifier)","integer (inference steps, typically 20-100)","integer (output dimensions, e.g., 512x512, 768x768)"],"output_types":["image (binary PNG/JPEG/WebP)","string (image URL or base64-encoded data)","metadata object (generation time, model used, seed if applicable)"],"categories":["image-visual","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcpcnimage-ai-generation-mcp__cap_2","uri":"capability://tool.use.integration.mcp.resource.discovery.and.schema.validation.for.image.generation.parameters","name":"mcp resource discovery and schema validation for image generation parameters","description":"Implements MCP's resource discovery protocol to advertise available image generation models, supported dimensions, and parameter constraints as machine-readable schemas. The MCP server validates incoming generation requests against these schemas before forwarding to Nano Banana Pro, catching invalid parameters early and providing helpful error messages to clients.","intents":["I want to know what image generation models are available without reading documentation","I need to validate that my generation parameters are compatible before making an API call","I want my IDE or MCP client to autocomplete and type-check image generation parameters"],"best_for":["Developers building MCP-aware IDEs or code editors with parameter autocomplete","Teams standardizing on MCP and needing discoverable tool schemas","Automated systems that need to validate parameters programmatically before generation"],"limitations":["Schema discovery is static — does not reflect real-time changes to Nano Banana Pro's available models or rate limits","No dynamic capability negotiation — client must handle schema mismatches if Nano Banana Pro API changes","Schema validation happens only at the MCP layer — Nano Banana Pro may still reject valid-looking requests due to backend constraints"],"requires":["MCP-compatible client that supports resource discovery (e.g., Claude Desktop 0.3+)","Nano Banana Pro API documentation or schema file to bootstrap available models"],"input_types":["MCP resource discovery request (no direct input from user)"],"output_types":["JSON schema (model list, parameter constraints, dimension options)","structured metadata (model capabilities, pricing tier, inference time estimates)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcpcnimage-ai-generation-mcp__cap_3","uri":"capability://safety.moderation.api.key.management.and.authentication.for.nano.banana.pro","name":"api key management and authentication for nano banana pro","description":"Handles secure storage and injection of Nano Banana Pro API credentials into outbound requests. The implementation supports environment variable configuration and optional credential validation at startup, ensuring that authentication failures are caught early rather than during image generation requests.","intents":["I want to securely configure my Nano Banana Pro API key without hardcoding it in my application","I need to validate that my API key is valid before attempting to generate images","I want to rotate API keys without restarting my MCP server"],"best_for":["Production deployments where API keys must be managed securely","Teams using environment-based configuration (Docker, Kubernetes, CI/CD)","Developers who want fail-fast validation of credentials at startup"],"limitations":["No built-in key rotation or expiration management — relies on external secret management systems","Credentials stored in environment variables are vulnerable to process memory dumps or log leaks","No support for multiple API keys or per-user authentication — single shared key only","No audit logging of API key usage or generation requests"],"requires":["Environment variable NANO_BANANA_PRO_API_KEY set before MCP server startup","Valid Nano Banana Pro API key with active subscription"],"input_types":["string (API key from environment)"],"output_types":["boolean (authentication validation result)","error message (if validation fails)"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcpcnimage-ai-generation-mcp__cap_4","uri":"capability://safety.moderation.error.handling.and.user.friendly.failure.messages.for.generation.requests","name":"error handling and user-friendly failure messages for generation requests","description":"Catches failures from the Nano Banana Pro API (rate limits, invalid prompts, quota exceeded, network timeouts) and translates them into human-readable error messages that Claude can relay to users. The implementation maps HTTP status codes and API error responses to actionable guidance (e.g., 'quota exceeded — upgrade your plan' or 'prompt contains blocked content').","intents":["I want to understand why an image generation request failed without debugging API responses","I need Claude to suggest next steps when generation fails (e.g., simplify the prompt, upgrade the plan)","I want to distinguish between transient failures (retry) and permanent failures (user action required)"],"best_for":["User-facing applications where error clarity is critical for UX","Developers building resilient agents that need to handle failures gracefully","Teams supporting non-technical users who need clear guidance on what went wrong"],"limitations":["Error messages depend on Nano Banana Pro's API error responses — if the API returns generic errors, so will this capability","No automatic retry logic — clients must implement their own retry strategies","Error classification is static — does not adapt to new failure modes introduced by Nano Banana Pro API changes","No structured error codes — error information is primarily text-based, making programmatic error handling difficult"],"requires":["Nano Banana Pro API error responses (HTTP status codes and error payloads)","MCP client capable of displaying error messages to users"],"input_types":["HTTP response (status code and error body from Nano Banana Pro)"],"output_types":["string (human-readable error message)","optional: structured error object with code, severity, and suggested actions"],"categories":["safety-moderation","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+ (MCP SDK requirement)","Valid Nano Banana Pro API key with image generation quota","MCP-compatible client (Claude Desktop, custom MCP host, or compatible IDE)","@mcpcn/image-ai-generation-mcp package installed via npm","Valid Nano Banana Pro API key with sufficient image generation credits","Text prompt (minimum ~10 characters for meaningful generation)","Optional: model name parameter (defaults to Nano Banana Pro's default model if not specified)","MCP-compatible client that supports resource discovery (e.g., Claude Desktop 0.3+)","Nano Banana Pro API documentation or schema file to bootstrap available models","Environment variable NANO_BANANA_PRO_API_KEY set before MCP server startup"],"failure_modes":["Dependent on Nano Banana Pro API availability and rate limits — no local fallback or caching layer","No built-in retry logic or exponential backoff for failed generation requests","Synchronous request-response model only — no support for long-polling or webhook callbacks for async generation","No image format negotiation — output format determined entirely by Nano Banana Pro API defaults","No prompt optimization or enhancement — raw user prompts sent directly to Nano Banana Pro without semantic improvement","Limited model selection — only models available through Nano Banana Pro's current API offerings","No image-to-image or inpainting capabilities — text-to-image only","Generation latency depends entirely on Nano Banana Pro backend performance (typically 10-60 seconds per image)","Schema discovery is static — does not reflect real-time changes to Nano Banana Pro's available models or rate limits","No dynamic capability negotiation — client must handle schema mismatches if Nano Banana Pro API changes","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.2,"ecosystem":0.45,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.904Z","last_scraped_at":"2026-05-03T14:23:58.638Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-mcpcnimage-ai-generation-mcp","compare_url":"https://unfragile.ai/compare?artifact=npm-mcpcnimage-ai-generation-mcp"}},"signature":"yMyc+BpNRnjnnJQw88ACiK26ajAt9sea4yWSAD4IJHyToZDR0MvnKCjM6YxRFvL189s6mquHEv8Yljk12AJ3AA==","signedAt":"2026-06-22T03:17:13.750Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-mcpcnimage-ai-generation-mcp","artifact":"https://unfragile.ai/npm-mcpcnimage-ai-generation-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=npm-mcpcnimage-ai-generation-mcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}