{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_antivirusakash-blog-imagegen-mcp","slug":"antivirusakash-blog-imagegen-mcp","name":"OpenAI Image Generator","type":"mcp","url":"https://smithery.ai/servers/antivirusakash/blog-imagegen-mcp","page_url":"https://unfragile.ai/antivirusakash-blog-imagegen-mcp","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","openai","image-generation","smithery:antivirusakash/blog-imagegen-mcp"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_antivirusakash-blog-imagegen-mcp__cap_0","uri":"capability://tool.use.integration.mcp.standardized.image.generation.via.openai.dall.e","name":"mcp-standardized image generation via openai dall-e","description":"Exposes OpenAI's image generation capabilities through the Model Context Protocol (MCP) server interface, allowing any MCP-compatible client to invoke image generation without direct API integration. The server acts as a protocol adapter that translates MCP tool calls into OpenAI API requests, handling authentication, request marshaling, and response serialization back to the MCP client.","intents":["I want to add image generation to my Claude desktop app without writing custom OpenAI integration code","I need to call image generation from an MCP-aware application without managing API keys directly in my client","I want to standardize image generation across multiple tools using a single MCP interface"],"best_for":["MCP client developers building Claude plugins or integrations","teams standardizing on MCP for tool orchestration across multiple AI applications","developers wanting to abstract OpenAI image generation behind a protocol-agnostic interface"],"limitations":["Requires OpenAI API key to be configured in the MCP server environment — no built-in key management or rotation","Single-threaded request handling may cause queuing under high concurrent load","No built-in caching of generated images — each request hits the OpenAI API","Limited to OpenAI's DALL-E models; no support for alternative image generation providers (Stability AI, Midjourney, etc.)","MCP protocol overhead adds ~50-100ms latency per request compared to direct API calls"],"requires":["OpenAI API key with image generation permissions","MCP-compatible client application (Claude, custom MCP client, etc.)","Network connectivity to OpenAI API endpoints","Node.js 16+ or Python 3.8+ (depending on MCP server implementation)"],"input_types":["text prompt (string)","optional: image size parameter (256x256, 512x512, 1024x1024)","optional: image quality parameter (standard, hd)","optional: number of images to generate (1-10)"],"output_types":["image URL (string, publicly accessible for 1 hour)","base64-encoded image data (optional)","structured metadata (generation timestamp, model used, prompt echo)"],"categories":["tool-use-integration","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_antivirusakash-blog-imagegen-mcp__cap_1","uri":"capability://text.generation.language.text.to.image.prompt.translation.and.parameter.mapping","name":"text-to-image prompt translation and parameter mapping","description":"Accepts natural language image descriptions and maps them to OpenAI DALL-E's supported parameters (size, quality, style modifiers). 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The server manages concurrent OpenAI API calls (respecting rate limits) and returns all generated images with their metadata in a structured response. Implementation likely uses async/await patterns with configurable concurrency limits to avoid overwhelming the OpenAI API.","intents":["I want to generate 5 variations of an image concept in one API call instead of making 5 separate requests","I need to batch-generate images for a content pipeline without manually orchestrating multiple sequential calls","I want to generate images for multiple product variations simultaneously to speed up my workflow"],"best_for":["content creators generating multiple image variations for A/B testing","e-commerce teams bulk-generating product images","developers building batch processing pipelines that need image generation as a step"],"limitations":["OpenAI API rate limits apply per account — batch requests may be throttled if account has low rate limits","Each image in a batch incurs separate API costs; no bulk discount or batch pricing from OpenAI","Batch requests are not atomic — if one image fails, others still succeed, requiring client-side error handling per image","No built-in retry logic for failed images within a batch; clients must implement their own retry strategy","Maximum batch size likely limited by OpenAI's concurrent request limits (typically 3-5 concurrent requests per account)"],"requires":["Array of text prompts (1-10 items) or single prompt with count parameter (1-10)","OpenAI API key with sufficient rate limit quota","Sufficient API credits to cover all images in the batch"],"input_types":["array of text prompts (strings)","OR single prompt string + count parameter (integer, 1-10)","optional: shared size parameter (applies to all images in batch)","optional: shared quality parameter (applies to all images in batch)"],"output_types":["array of image objects, each containing: URL, generation metadata, prompt used","batch status object (total requested, successful, failed)","error details for any failed images (error code, reason)"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_antivirusakash-blog-imagegen-mcp__cap_3","uri":"capability://safety.moderation.image.generation.with.error.handling.and.fallback.responses","name":"image generation with error handling and fallback responses","description":"Implements comprehensive error handling for OpenAI API failures, including rate limit detection, authentication errors, invalid prompt rejection, and network timeouts. The server returns structured error responses that distinguish between client errors (invalid input, policy violations) and server errors (API outages, rate limits), allowing MCP clients to implement appropriate retry strategies or user-facing error messages.","intents":["I want to know why an image generation failed and whether I should retry or fix my prompt","I need to distinguish between temporary API outages and permanent policy violations so I can handle them differently","I want my application to gracefully degrade when OpenAI's API is unavailable instead of crashing"],"best_for":["production applications requiring robust error handling and user feedback","teams building resilient workflows that need to distinguish transient vs permanent failures","developers implementing retry logic that depends on error classification"],"limitations":["Error messages are limited to OpenAI's API error responses — no custom error enrichment or context from the MCP server","No built-in exponential backoff or automatic retry logic — clients must implement their own retry strategy","Rate limit errors may not include precise retry-after timing; clients must guess or use default backoff","Policy violation errors are opaque — OpenAI doesn't provide detailed reasons why a prompt was rejected","Network timeout handling depends on MCP client's timeout configuration; server has no control over client-side timeouts"],"requires":["Valid OpenAI API key (for authentication error detection)","Network connectivity to OpenAI API (for timeout/connectivity error detection)","MCP client capable of handling structured error responses"],"input_types":["text prompt (string)","optional: size, quality, and other generation parameters"],"output_types":["on success: image URL and metadata","on failure: structured error object containing: error code (rate_limit_exceeded, invalid_request_error, authentication_error, etc.), error message, retry-after hint (if available), timestamp"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_antivirusakash-blog-imagegen-mcp__cap_4","uri":"capability://tool.use.integration.openai.api.credential.management.and.request.signing","name":"openai api credential management and request signing","description":"Manages OpenAI API authentication by accepting and securely storing the API key, then automatically including it in all outbound requests to OpenAI's image generation endpoints. 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