Universal Poison Armor
Related Servers
Alternatives to Universal Poison Armor
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceMCP server that provides tools to scan text and URLs for prompt injection attacks, protecting AI agents from adversarial inputs.MIT
- AlicenseNot gradedqualityDmaintenanceMCP server that provides runtime defense for AI agents, protecting against prompt injection, data exfiltration, and other adversarial attacks through a ranked pipeline of up to 36 inline defenses and 3 output scanners.3Apache 2.0

RAGSHIELDofficial
FlicenseNot gradedqualityCmaintenanceRAG corpus poisoning detector that scans for embedding anomalies and backdoor triggers, with an MCP server for AI agent integration.1-- FlicenseNot gradedqualityBmaintenanceEnables deterministic detection and neutralization of adversarial prompt injections and override attempts in AI agent workflows via a zero-dependency MCP server, providing structured telemetry and low-latency validation.7-
- AlicenseNot gradedqualityCmaintenanceA multi-agent AI security layer that protects LLMs from prompt injection, jailbreaks, and policy violations via MCP tools.MIT
- AlicenseAqualityDmaintenanceAn MCP server that provides a guarded interface to the mem9 persistent memory backend, protecting AI agents against prompt injection, secret leakage, and memory poisoning.6MIT
TDQS
Scored across 3 tools
Each tool targets a clearly distinct attack surface: single-document sanitization, dataset-level anomaly detection, and multi-source consensus verification. The descriptions include explicit WHEN NOT TO USE cross-references that direct the agent to the correct sibling tool, leaving no ambiguity.
All three tool names follow the same snake_case verb_noun pattern: sanitize_document, scan_dataset_for_anomalies, and verify_article_consensus. The verbs are specific and accurately describe each tool's core action.
Three tools is well-scoped for this specialized defensive server, with one tool covering each major poisoning vector: input text, training/retrieval datasets, and web-sourced consensus claims. Every tool earns its place, and there are no redundant or filler tools.
The tool set covers the core defense workflow: sanitize untrusted input, detect poisoned clusters in datasets, and verify whether apparent consensus is authentic. A minor gap is the lack of a dedicated tool for reading or querying the security_audit.json log that all tools append to, but this is workable via external file access.