ZeroTrust Log AI Secure, Context-Aware Log Analysis for Modern Infrastructure ZeroTrust Log AI is a high-performance MCP server built for SREs and DevOps engineers who need rapid root-cause analysis without compromising data security. It combines large-context AI with a Zero Trust redaction layer — so your secrets never leave your environment. The Problem Modern observability forces an impossible trade-off:

Manual analysis → slow and error-prone Cloud AI tools → risk exposing tokens, IPs, and credentials

During a production incident, neither is acceptable. The Solution: Read → Redact → Resolve ZeroTrust Log AI acts as a secure intelligence layer between your infrastructure and AI. Sensitive data is scrubbed locally before any AI processing occurs. Core Capabilities

Zero Trust Redaction — API keys, bearer tokens, JWTs, emails, and IPs are automatically redacted before leaving your environment Large-Scale Log Correlation — processes thousands of lines, detects cross-service failure patterns, identifies microservice dependencies SRE-Optimized Output — root cause, ready-to-run kubectl / docker / systemctl commands, minimal noise Temporal Root Cause Analysis — correlates events across distributed services to find the originating failure

How It Works

Ingest — connect via MCP to your IDE (Cursor, Claude, etc.) or CLI Scrub — sensitive data is redacted locally, never sent to AI Analyze — cleaned logs processed by Gemini 2.5 Flash Resolve — structured report: root cause, suggested fix, explanation

Example: Microservice Failure Cascade A Redis failure triggers 499 errors at ingress and ECONNREFUSED in app logs. ZeroTrust Log AI correlates events across services, identifies the root cause (DNS misconfiguration or OOM-killed pod), and returns exact remediation commands. Technical Specifications

Language: TypeScript / Node.js Protocol: MCP (2025-06-18) AI Backend: Gemini 2.5 Flash Deployment: Cloud Run via MCPize / self-hostable Security: Local-first redaction, no log persistence