Connects Vunet vuSmartMaps with AI assistants for natural language querying of observability data.
Sponsored
The Vunet Model Context Protocol (MCP) Server is designed to bridge Vunet vuSmartMaps, a multi-tenant observability platform akin to Dynatrace MCP, with AI assistants and other MCP-compatible clients. It enables users to query over 80 data models, including Kubernetes metrics, application traces, transaction volumes, and custom data, using natural language. The server supports flexible querying with relative and absolute time ranges, dynamic filters, time-shift comparisons, and secure authentication methods like username/password or bearer tokens, all while managing sessions automatically.
Key Features
01Comprehensive Data Access to 80+ data models (Kubernetes, traces, infrastructure, etc.)
02Secure Authentication with session management and automatic token refresh
03Flexible Querying with relative/absolute time ranges, filters, and time-shift comparisons
040 GitHub stars
05Easy Installation via npm for global or local use
06Multi-Tenant Support for connecting to multiple Vunet tenants
Use Cases
01Creating interactive dashboards for Kubernetes health and other infrastructure metrics
02Querying Vunet observability data (metrics, traces, logs) using natural language through AI assistants like Claude or ChatGPT
03Generating performance analysis reports of application traces and error rates across multiple tenants
