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Enkrypt AI MCP Server

Official
by enkryptai

guardrails_detect

Identify sensitive content in text using customizable detectors for injection attacks, PII, NSFW content, toxicity, and policy violations. Returns detailed safety assessments for analysis.

Instructions

Detect sensitive content using Guardrails.

Args: ctx: The context object containing the request context. text: The text to detect sensitive content in. detectors_config: Dictionary of detector configurations. Each key should be the name of a detector, and the value should be a dictionary of settings for that detector. Available detectors and their configurations are as follows:

- injection_attack: Configured using InjectionAttackDetector model. Example: {"enabled": True} - pii: Configured using PiiDetector model. Example: {"enabled": False, "entities": ["email", "phone"]} - nsfw: Configured using NsfwDetector model. Example: {"enabled": True} - toxicity: Configured using ToxicityDetector model. Example: {"enabled": True} - topic: Configured using TopicDetector model. Example: {"enabled": True, "topic": ["politics", "religion"]} - keyword: Configured using KeywordDetector model. Example: {"enabled": True, "banned_keywords": ["banned_word1", "banned_word2"]} - policy_violation: Configured using PolicyViolationDetector model. Example: {"enabled": True, "need_explanation": True, "policy_text": "Your policy text here"} - bias: Configured using BiasDetector model. Example: {"enabled": True} - copyright_ip: Configured using CopyrightIpDetector model. Example: {"enabled": True} - system_prompt: Configured using SystemPromptDetector model. Example: {"enabled": True, "index": "system_prompt_index"} Example usage: { "injection_attack": {"enabled": True}, "nsfw": {"enabled": True} }

Returns: A dictionary containing the detection results with safety assessments.

Input Schema

NameRequiredDescriptionDefault
detectors_configYes
textYes

Input Schema (JSON Schema)

{ "properties": { "detectors_config": { "additionalProperties": true, "title": "Detectors Config", "type": "object" }, "text": { "title": "Text", "type": "string" } }, "required": [ "text", "detectors_config" ], "title": "guardrails_detectArguments", "type": "object" }

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