"Generating Metrics" matching MCP servers:

Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.

Seamlessly bring real-time production context—logs, metrics, and traces—into your local environment to auto-fix code faster.

Enables AI assistants and LLMs to query SigNoz observability data (metrics, traces, logs, alerts, dashboards) using natural language.

An open-source MCP server that protects AI agents at runtime by evaluating every tool call against YAML policies and generating audit trails.

A Model Context Protocol server that enables AI agents to interact directly with Prometheus metrics data through natural language queries.

MCP server that exposes live host metrics (CPU, memory, processes, network) to Cursor/Claude via /proc and optional eBPF, enabling system monitoring dashboards and natural language queries.

Provides tools to search, query, and visualize Prometheus metrics, returning results in JSON format for AI analysis.

Enables querying Prometheus metrics, performing cluster diagnostics, and analyzing resource usage through natural language, with automatic Kubernetes connectivity.

Enables assistants to read account data (tunnels, usage, metrics, tokens, invoices, domains, notifications, cloud apps) and start/stop tunnels via the tunnels.io API and CLI.

Probe LLM API endpoints and report health metrics including time to first token, latency, and throughput.

An MCP server for Everstake's non-custodial staking data across 130+ networks: live APY, uptime metrics, rewards calculator, integrations, security and compliance. Built for asset managers, custodians, and exchanges evaluating institutional staking.

MCP server that reads Duplicacy backup metrics from a Prometheus exporter and exposes them to LLMs for monitoring backup status, progress, and health.

swagger-mcp is a tool designed to scrape Swagger UI by extracting the swagger.json file and dynamically generating well-defined mcp tools at runtime. These tools can be utilized by the MCP client for further tool selection.

Enables AI assistants to interact with DataDog's observability platform through a standardized interface. Supports monitoring infrastructure, managing events, analyzing logs and metrics, and automating operations like alerts and downtimes.

Enables AI agents to query Zabbix for current problems, host investigations, alert triage, metrics, and maintenance operations through task-shaped tools with bounded JSON output and human-approval safeguards for any changes.

This MCP server provides tools to interact with the Pacer API for portfolio management, performance metrics, and PMS integration, but it is now retired and users should switch to the in-process Pacer MCP connector.