Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.
Demonstrates agent-native platform onboarding with human-in-the-loop API key provisioning, plus live usage and rate-limit queries via Anthropic Admin APIs.
Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.
Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.
Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.
Provides AI agents with real-time access to live Azure infrastructure, including AKS cluster health, resource management, policy validation, and Terraform analysis through a Model Context Protocol interface.
Enables ingestion and full-text search of Windows application logs via MCP tools. Supports dual-backend indexing with Elasticsearch and SQLite for fast retrieval.
Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.
Enables AI assistants to manage multi-cloud resources (AWS, Azure, GCP) including resource operations, cost analysis, monitoring metrics, and security compliance checks through natural language commands.
A FastAPI-based server that enables executing SQL queries, managing database connections, and retrieving analytics reports through MCP-integrated endpoints. It allows users to interact with database schemas, performance metrics, and access logs using structured queries.
Enables AI assistants to interact with SMB platform APIs for querying business data, managing tasks, accessing connectors, dashboards, and monitoring security.
A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports.
An open-source MCP server for managing Proxmox environments, including nodes, virtual machines, and containers. It enables users to perform inventory checks, status monitoring, and control operations directly through MCP-compatible tools.
A high-performance MCP server integrated with a Django analytics dashboard, featuring 19 tools for AI interaction tracking, AST code analysis, and real-time token efficiency metrics.
A robust Model Control Protocol server that enables AI agents to access real-time cyber threat intelligence and detailed information about vulnerabilities, threat actors, malware, and other cyber-security entities.