"Generating Metrics" matching MCP servers:

Provides read-only access to host system metrics (CPU, memory, disk), Docker container health/logs, and sandboxed log file analysis via MCP tools, enabling AI agents to monitor enterprise infrastructure safely.

Provides access to Prometheus metrics and queries through standardized Model Context Protocol interfaces, allowing AI assistants to execute PromQL queries and analyze metrics data.

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.

Provides MCP tools for querying LinkYun operations metrics, including listing metrics, querying metrics, managing agents, and home recommendations, by forwarding requests to the LinkYun Agent Ops HTTP API.

Enables LLM clients to ask natural-language questions about FABRIC Testbed infrastructure metrics, with responses grounded in fixed Grafana/PromQL queries for node, switch, and link metrics.

Provides access to Prometheus metrics and queries, allowing AI assistants to execute PromQL queries and analyze metrics data through standardized MCP interfaces.

Query Prometheus from CLI or any MCP client, with retries, caching, and an optional metrics exporter.

Exposes the Swarmia Export API as tools for AI assistants to query engineering metrics through natural language. It enables retrieval of DORA metrics, pull request cycle times, investment balances, and FTE effort reports.

Comprehensive system diagnostics and monitoring server providing detailed hardware information, performance metrics, and optimization recommendations.

Exposes a metrics query API to AI assistants, allowing them to issue queries and interact with the server's tools such as ping.

Gives AI agents real-time access to system metrics, process management, and container orchestration.

Enables AI assistants to query FusionReactor Cloud metrics, logs, and alerts via MCP tools.

Enables exploration of Kubernetes metrics, logs, traces, and service graph data via simple tools.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Provides Claude with read-only access to PC diagnostics including hardware specs, live performance metrics, disk usage, network checks, and more, enabling natural language queries about PC health and performance.

An MCP server that automatically instruments Python AI agents with the ioa-observe-sdk, adding OpenTelemetry-based tracing, metrics, and logs with zero manual effort.

MCP server for Prometheus metrics and observability. Give Claude (or any MCP-capable agent) read access to your Prometheus instance — query metrics with PromQL, inspect active alerts, and explore scrape targets without leaving the conversation. Tools: prometheus_list_metrics, prometheus_query, prometheus_query_range, prometheus_list_alerts, prometheus_list_targets.

Exposes an observability REST API as MCP tools, enabling incident investigation through automated correlation of deploys with errors, log and metrics queries.

Enables AI assistants to read-only explore OpenObserve: list streams, inspect schemas, and run bounded SQL searches over logs, metrics, and traces without write access.