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AtlasCloudAI

Atlas Cloud MCP Server (Image / Video / LLM APIs)

by AtlasCloudAI

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
ATLASCLOUD_API_KEYYesAtlas Cloud API Key used to authenticate with the AI API aggregation platform. Get one free at atlascloud.ai/console/api-keys

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
atlas_search_docsA

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

atlas_list_modelsA

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

atlas_get_model_infoA

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

atlas_generate_imageA

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"}

atlas_generate_videoA

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"}

atlas_chatA

Send a chat completion request to an LLM model via Atlas Cloud API (OpenAI-compatible format).

Args:

  • model (string, required): The LLM model ID (e.g., "deepseek-ai/deepseek-v3.2", "qwen/qwen3-32b")

  • messages (array, required): Array of message objects with "role" and "content" fields. Roles: "system", "user", "assistant"

  • temperature (number, optional): Sampling temperature, 0-2. Default: 1

  • max_tokens (number, optional): Maximum tokens in the response

  • top_p (number, optional): Nucleus sampling parameter, 0-1. Default: 1

Returns: The LLM response including the generated message, token usage, and finish reason.

Examples:

  • model="deepseek-ai/deepseek-v3.2", messages=[{"role": "user", "content": "Hello"}]

  • model="qwen/qwen3-32b", messages=[{"role": "system", "content": "You are a helpful assistant"}, {"role": "user", "content": "Explain quantum computing"}], temperature=0.7

atlas_get_predictionA

Check the status and result of an image/video generation task.

Use this after submitting a generation request to check if the result is ready.

If the status is still "processing" or "starting", wait a moment and try again.

When the result is ready (status is "completed" or "succeeded"), the output URLs will be returned. You should then:

  1. Show the output URLs to the user

  2. Ask the user if they want to download the file to their local machine (you can use curl or wget to download it)

Args:

  • prediction_id (string, required): The prediction ID returned from a generation request

Returns: The current status and output of the generation task.

Examples:

  • prediction_id="pred_abc123" -> check generation status

atlas_quick_generateA

One-step image or video generation - automatically finds the model by keyword, fetches its schema, builds parameters, and submits the task.

IMPORTANT: If this tool fails to find a model, call atlas_list_models first to get the exact model list, then use atlas_generate_image or atlas_generate_video with the exact model ID instead.

The tool searches for models by keyword matching against model ID, display name, and tags. After getting the prediction ID, use atlas_get_prediction to check the result.

Args:

  • model_keyword (string, required): A keyword to search for the model. Use the model's display name or key words (e.g., "Nano Banana", "Seedream", "Kling", "Vidu", "Seedance")

  • type (string, required): Generation type: "Image" or "Video"

  • prompt (string, required): Text description of what to generate

  • image_url (string, optional): Source image URL for image-to-video or image editing models

  • extra_params (object, optional): Additional model-specific parameters to override defaults (e.g., {"duration": 10, "aspect_ratio": "16:9"})

Returns: A prediction ID to check the result with atlas_get_prediction.

Examples:

  • model_keyword="nano banana", type="Image", prompt="a cute cat in space"

  • model_keyword="seedream v5", type="Image", prompt="sunset over mountains"

  • model_keyword="kling v3", type="Video", prompt="a rocket launching", extra_params={"duration": 5}

  • model_keyword="seedance", type="Video", prompt="camera panning right", image_url="https://example.com/photo.jpg"

atlas_upload_mediaA

Upload a local image or media file to Atlas Cloud and get a publicly accessible URL.

Use this tool when you need to provide an image URL to image-editing or image-to-video models, but only have a local file path.

Workflow:

  1. Upload the local file with this tool to get a URL

  2. Use the returned URL as the "image_url" parameter in atlas_generate_image, atlas_generate_video, or atlas_quick_generate

Supported file types: images (jpg, png, webp, etc.), videos, and other media files.

IMPORTANT: This upload is intended for temporary use with Atlas Cloud generation tasks only. Uploaded files may be cleaned up periodically. Do NOT use this as a permanent file hosting service. Abuse (e.g., bulk uploads unrelated to generation tasks) may result in API key suspension.

Args:

  • file_path (string, required): Absolute path to the local file to upload

Returns: The publicly accessible download URL of the uploaded file.

Examples:

  • file_path="/Users/me/photos/cat.jpg" -> uploads and returns a URL like "https://atlas-img.oss-accelerate-overseas.aliyuncs.com/media/xxx.jpg"

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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