An MCP server that enables conversational interaction with Wazuh SIEM, allowing users to investigate alerts, hunt threats, tune false positives, edit rules, and run security actions via natural language.
Enables observability and governance for local LLMs via Ollama, including auditing model usage, scanning prompts for secrets/PII, and enforcing allow/deny policies.
Provides read-only, governance-audited operations for OLVM and oVirt 4.5 engines, enabling inventory, health, capacity, and diagnosis queries over MCP and CLI with audit logging and budget guards.
Governed AI-ops for Ceph, providing root-cause health analysis and guarded destructive operations via a built-in governance harness with risk tiers, audit, and undo recording.
An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.
Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.
Presents a plausible, tool-rich workspace surface — file reading, credential listing, command execution, database queries, and configuration retrieval — that returns only synthetic results while logging every connection, tool call, and argument received. It enables researchers to measure what MCP clients and agents actually do when handed dangerous-sounding tools, including whether they follow injected instructions or complete a retrieve-then-use credential chain.
Enables AI assistants to query system health, metrics, service reconnaissance, run multi-node patrols, and send incident alerts across distributed infrastructure through MCP tools.
Compresses log files into templates and statistics using Drain3, and exposes them to AI assistants via an MCP server for efficient log monitoring and anomaly detection.
MCP server for Grubhub Data Platform operations, providing 40+ tools across 18 service categories for data platform management, observability, analytics, and collaboration.
MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.
Enables an LLM agent to investigate a Kong Gateway through fourteen read-only, schema-validated tools and a deterministic diagnostic engine, so it can trace routes, services, plugins and upstream health and explain faults such as why authentication is failing on a path. Every fact comes from the gateway itself, and the model only selects tools and writes the evidence-backed explanation.
Model Context Protocol server for Verlon AI that exposes gates, logs, recommendations, and experiments as MCP tools, enabling coding agents to inspect and manage AI infrastructure natively.
Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.
A MCP server for tracking AI usage metrics and structured logs across applications. Monitor model calls, analyze usage patterns, track costs, and debug AI interactions.
MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.
Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.
