"A music streaming service" matching MCP servers:

这是面向智能运维场景的 MCP 工具服务，让 Agent 能够按需检索日志内容并获取主机与应用的监控指标数据。它把实时的日志与指标证据接入 Plan-Execute-Replan 诊断流程，从而支撑自动故障排查与根因分析。

Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.

MCP server that exposes Avangenio's service status by fetching and parsing status.avangenio.com/data.txt into normalized JSON.

Exposes a Raspberry Pi homelab's systemd service health, disk usage, CPU temperature, and LAN game-server status as read-only MCP tools, letting MCP clients answer questions like "how's the homelab doing?" without SSHing in manually.

An MCP server for streaming and searching macOS Console.app and iOS device logs, enabling real-time log access and debugging through natural language.

A professional-grade MCP server that enables AI assistants to monitor web services, APIs, and HTTP endpoints with enterprise-level security.

Provides tools to communicate with a service dependency API, enabling users to query and interact with service relationship data and dependency mappings.

Model Context Protocol server for managing and diagnosing GlassFlow streaming pipelines, exposing pipeline CRUD, metrics queries, log search, and a composite diagnostic tool as MCP tools that AI agents can call over SSE transport.

A Model Context Protocol (MCP) server for the Pingera monitoring service, providing seamless integration between AI models and monitoring data.

Enables a local AI agent to investigate service incidents by querying read-only telemetry such as service health, metrics, logs, and traces, then produce verifiable assessments with evidence links and uncertainty.

Enables triggering, streaming, and reviewing autonomous production-incident investigations directly from your editor, with human-gated approval for any mutating actions.

Ships only the MCP server, not the recorder. Recording works by wrapping a process on the host — a local proxy, a PATH shim, a shadow git index. None of that survives a container boundary, so orca record inside here would watch an empty namespace. What does travel is the read side: the six MCP tools serve runs that already exist on disk, so a client mounts its .orca directory and r

Enables users to log AI tool activity without conversation text and contribute back only user-approved, small-cell-suppressed counts through a local MCP interface.

Enables AI incident-response agents to connect over MCP to a simulated service environment, receive alerts, gather diagnostic evidence, execute safe SOP actions, and verify recovery.

A local TypeScript MCP gateway that unifies SSH, Prometheus, and MySQL tools under a single loopback HTTP service, featuring a web console for configuration and health monitoring.

Enables agents to access web analytics statistics via OAuth, providing a privacy-first, cookie-free analytics service.

Enables AI assistants to query system health, metrics, service reconnaissance, run multi-node patrols, and send incident alerts across distributed infrastructure through MCP tools.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Enables any MCP client to watch a running DSH agent and steer it mid-flight, streaming thinking, tool and file notifications while sharing intent and exposing a floor lock that denies the agent's writes while held. It also lets clients interrupt the current turn with an injected alert and delegate reviews through an on-disk inbox.

A Model Context Protocol server for Kubernetes that provides full resource coverage and advanced troubleshooting tools via HTTP chunked streaming. It enables users to manage clusters and diagnose complex issues like pod crashloops through specialized prompts and standard kubectl-like operations.

A TypeScript implementation of a Model Context Protocol server that connects to Sentry error tracking service, allowing AI models to query and analyze error reports and events.

A read-only MCP server that exposes Azure incident-investigation tools for a single App Service and its Application Insights telemetry, enabling an agent to correlate deployment history, platform metrics, and transaction traces.

Enables read-only querying and analysis of Kibana logs through a logged-in sid Cookie, including keyword/time/index searches, traceId lookups, surrounding log context, and aggregations by service, level, or host. It also validates Kibana connection status and redacts sensitive fields such as cookies, tokens, and passwords.

Enables read-only querying of a local Grafana Loki instance, providing log search, service listing, and health check capabilities.

Exposes the shared health-check service as an MCP tool, letting clients query status, uptime, and version through the streamable HTTP endpoint.

Enables live tracing and observability of MCP tool calls, persisting execution traces to MongoDB and streaming them in real time to a dashboard.

A FastMCP server that provides DataDog log search and monitoring with service-aware filtering, preview-execute workflow, and response size safeguards.

MCP server that exposes AI credit usage data from OpenMeter to the TAIS AI chat service, automatically scoped to the calling tenant and restricted to admin users.

Streams real-time log context from Amazon MSK to a Bedrock AI agent for anomaly detection and root cause analysis. Enables AI-powered monitoring with WebSocket push and IAM authorization.

Enables business services to push error logs and generate diagnostic reports using MCP tools for log searching, code querying, and report generation.