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Enkrypt AI MCP Server

Official
by enkryptai

add_deployment

Create a new deployment by configuring input and output guardrails, specifying policies, and enabling or blocking specific detectors to ensure AI safety and compliance.

Instructions

Add a new deployment using the provided configuration.

Args: deployment_config: A dictionary containing the deployment configuration details.

Example Usage: { "deployment_config": { sample_deployment_config = { "name": deployment_name, "model_saved_name": model_saved_name, "input_guardrails_policy": { "policy_name": policy_name, "enabled": True, "additional_config": { "pii_redaction": False #Add these if any additional detectors than that in the policy are needed }, "block": [ "injection_attack", # Could be any of the active detectors (Ask user if they want to block) "policy_violation" ] }, "output_guardrails_policy": { "policy_name": policy_name, "enabled": False, "additional_config": { "hallucination": False, #Add these if any additional detectors than that in the policy are needed "adherence": False, "relevancy": False }, "block": [ "nsfw" # Could be any of the active detectors (Ask user if they want to block) ] }, } }

Always ask user if they want to block any of the detectors in the policy for both input and output. (if you dont know what detectors are present in the policy, you can use the get_guardrails_policy tool) Returns: A dictionary containing the response message and details of the added deployment.

Input Schema

NameRequiredDescriptionDefault
deployment_configYes

Input Schema (JSON Schema)

{ "properties": { "deployment_config": { "additionalProperties": true, "title": "Deployment Config", "type": "object" } }, "required": [ "deployment_config" ], "title": "add_deploymentArguments", "type": "object" }

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