"Observability" matching MCP servers:

Provides comprehensive monitoring and observability for MCP server ecosystems with real-time health checks, performance metrics, distributed tracing, anomaly detection, and automated performance reports using OpenTelemetry and Prometheus.

Self-healing proxy for MCP servers that wraps tool calls with automatic retry, circuit breaker protection, and observability.

Enables AI agents to query New Relic observability data, including NRQL queries, entity searches, incident tracking, deployment history, and golden signals, via the Model Context Protocol.

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

A local MCP server for SkyPortal and Fritz that exposes astronomical transient data (photometry, spectra, classifications, observability) as tools for AI coding assistants.

MCP server for managing store replenishment, including listing stores, raising orders, checking order status, and viewing SKU reports with observability and key rotation handling.

eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime and Driver APIs via kernel uprobes and host events via tracepoints to build causal chains explaining GPU latency. 7 tools: get_check, get_trace_stats, get_causal_chains, get_stacks, run_demo, get_test_report, run_sql. Telegraphic compression reduces token usage ~60%. Supports stdio and HTTPS (TLS 1.3) transport.

Enables local-first observability for MCP agent workflows by recording tool calls, prompts, latency, and token usage in a local SQLite database, and provides tools for inspecting, comparing, exporting, and generating dashboards from traces.

Query Langfuse traces, schema and datasets, scores and metrics, debug exceptions, analyze sessions, and manage prompts. Full observability toolkit for LLM applications.

A FastMCP (Python) server for Rocket.Chat with 28 tools covering channels, messages, threads, DMs, files, users, and analytics, plus AI governance, observability, and security features.

Model Context Protocol server for Langfuse observability. Query traces, analyze accuracy, detect failures, track costs, debug latency, manage prompts and datasets.