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by AtlasCloudAI • Uncategorized
MCP server providing access to Atlas Cloud's AI models for image, video generation, and LLM chat.
Generate images using various AI models like Seedream and Qwen-Image.
Create videos with models such as Kling and Vidu.
Chat with OpenAI-compatible large language models like Qwen and DeepSeek.
Atlas Cloud MCP Server is an AI API aggregation platform that enables users to discover and interact with over 300 AI models including image generation, video generation, and large language models. It supports dynamic schema fetching for accurate API usage, media uploads for editing tasks, and quick one-step generation with automatic model selection. The server integrates with multiple IDEs, editors, and CLI tools, enhancing developer productivity by providing seamless access to diverse AI capabilities.
Search Atlas Cloud documentation, models, and API references by keyword. Returns matching models with descriptions, pricing, and links. For detailed API docs of a specific model, use atlas_get_model_info instead. Args: - query (string): Search keyword to match against model names, types, providers, tags, etc. Returns: Markdown-formatted list of matching models with key information. Examples: - "video generation" -> finds all video generation models - "deepseek" -> finds all DeepSeek models - "image edit" -> finds image editing models - "qwen" -> finds all Qwen models
List all available models on Atlas Cloud, optionally filtered by type. Args: - type (string, optional): Filter by model type. Options: "Text", "Image", "Video" Returns: Markdown-formatted list of models grouped by type, including model ID, description, provider, and pricing. Examples: - No params -> list all models - type="Image" -> list only image generation models - type="Video" -> list only video generation models - type="Text" -> list only LLM/text models
Get detailed information about a specific Atlas Cloud model, including API documentation, input/output schema, pricing, and usage examples. This tool fetches the model's OpenAPI schema and generates comprehensive API documentation with cURL examples. Args: - model (string): The model ID (e.g., "deepseek-ai/deepseek-v3.2", "kling-video/kling-v3.0-standard-text-to-video") Returns: Markdown-formatted model details including: - Model metadata (type, provider, context length, etc.) - Pricing information - Full API input/output schema with parameter descriptions - Required and optional parameters with defaults - cURL usage examples - Playground link Examples: - model="deepseek-ai/deepseek-v3.2" -> DeepSeek V3.2 model details and API docs - model="kling-video/kling-v3.0-standard-text-to-video" -> Kling video model API docs
Generate an image using Atlas Cloud API. This tool submits the generation request and returns immediately with a prediction ID. Use atlas_get_prediction to check the result later. IMPORTANT: The "model" parameter requires an exact model ID (e.g., "seedream/seedream-v5.0-lite-text-to-image"). If you don't know the exact model ID, you MUST first call atlas_list_models with type="Image" to find it. Do NOT guess model IDs. You should also use atlas_get_model_info to understand what parameters a specific image model accepts before calling this tool. Args: - model (string, required): The exact image model ID. Use atlas_list_models to find valid IDs. - params (object, required): Model-specific parameters as a JSON object. Each model has different parameters defined in its schema. Common params include "prompt", "image_size", "num_inference_steps", etc. Use atlas_get_model_info to see the full parameter list for your chosen model. Returns: A prediction ID to check the result with atlas_get_prediction. Examples: - model="seedream/seedream-v5.0-lite-text-to-image", params={"prompt": "a cat in space"} - model="qwen-image/qwen-image-text-to-image-plus", params={"prompt": "sunset over mountains", "image_size": "1024x1024"}
Generate a video using Atlas Cloud API. This tool submits the generation request and returns immediately with a prediction ID. Use atlas_get_prediction to check the result later. IMPORTANT: The "model" parameter requires an exact model ID (e.g., "kling-video/kling-v3.0-standard-text-to-video"). If you don't know the exact model ID, you MUST first call atlas_list_models with type="Video" to find it. Do NOT guess model IDs. You should also use atlas_get_model_info to see the full parameter list and schema for your chosen video model before calling this tool. Args: - model (string, required): The exact video model ID. Use atlas_list_models to find valid IDs. - params (object, required): Model-specific parameters as a JSON object. Parameters vary by model - use atlas_get_model_info to see available params. Common ones include: - "prompt" (string): Text description of the video - "image_url" (string): Source image for image-to-video models - "duration" (number): Video duration in seconds - "aspect_ratio" (string): e.g., "16:9", "9:16" Returns: A prediction ID to check the result with atlas_get_prediction. Video generation typically takes 1-5 minutes. Examples: - model="kling-video/kling-v3.0-standard-text-to-video", params={"prompt": "a rocket launching into space", "duration": 5} - model="bytedance/seedance-v1.5-pro-image-to-video", params={"prompt": "camera panning right", "image_url": "https://example.com/photo.jpg"}
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