Enkrypt AI MCP Server

Add a new model using the provided configuration.

Args: config: A dictionary containing the model configuration details. The structure of the ModelConfig is as follows: Example usage: { "model_saved_name": "example_model_name", # The name under which the model is saved. "model_version": "v1", # The version of the model. "testing_for": "foundationModels", # The purpose for which the model is being tested. (Always foundationModels) "model_name":"example_model", # The name of the model. (e.g., gpt-4o, claude-3-5-sonnet, etc.) "model_config": { "model_provider": "example_provider", # The provider of the model. (e.g., openai, anthropic, etc.) "endpoint_url":"https://api.example.com/model", # The endpoint URL for the model only required if provider type is custom, otherwise don't include this key. "apikey":"example_api_key", # The API key to access the model. "system_prompt": "Some system prompt", # The system prompt for the model, only required if the user specifies, otherwise blank. "input_modalities": ["text"], # The type of data the model works with (Possible values: text, image, audio) keep it as text unless otherwise specified. "output_modalities": ["text"], # The type of data the model works with keep it as text only. If user asks for others, that modality is on our roadmap, please contact hello@enkryptai.com if you need early access to this. }, } Ask the user for all the details before passing the config to the tool.

Returns: A dictionary containing the response message and details of the added model.