"A server or service related to @amap" matching MCP servers:

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

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

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

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

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

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

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Enables AI assistants to search, summarize, and inspect Kibana/OpenSearch Dashboards logs through the user's logged-in browser session, eliminating the need for API keys or service accounts.

Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.

An MCP server for Grafana Loki that enables LLMs to query, tail, and analyze logs, featuring fuzzy container-name matching, compact output, and tools for log patterns, volume, and label discovery. It can run as a local stdio server or a containerized HTTP service.

Enables AI assistants to look up uptime commitments, service credits, and per-service SLAs for cloud and SaaS vendors directly from SLA.directory.

Provides read-only access to the Cloudera Manager REST API, enabling inspection of cluster and service health, role configurations, logs, hosts, time-series metrics, events, commands, parcels, and audits through natural language. Every operation is a GET, so no configuration changes or service lifecycle actions are possible.

A specialized diagnostic framework that enables AI models to self-diagnose and fix MCP-related issues by analyzing logs, validating configurations, testing connections, and implementing solutions.

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 AI assistants to inspect uptime monitoring, incidents, status pages, alerts, dependencies, and reports. It also supports related changes such as opening incidents, posting updates, scheduling maintenance, adding monitors, and configuring alerts and reports.

Enables MCP clients to query and investigate logs, spans, metrics, RUM, alerts, cases, dashboards, and service catalog data through natural-language prompts over a hosted remote endpoint.

Enables AI assistants and other MCP clients to query live health and status of self-hosted homelab services through read-only HTTP probes, returning service registries and UP/DEGRADED/DOWN summaries without write access or secrets.

Enables AI agents to investigate production incidents by exposing service health, logs, and deployment data through MCP tools.

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 AI agents to search service logs, group errors by signature, compare a candidate run against a baseline for regressions, and correlate which problems from other services appear before or after an error. All results are computed by the tools rather than the language model, so agents can only explain findings the code produced.

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

Enables AI assistants to interact with tshark and related command-line tools for live packet capture, PCAP analysis, filtering, stream following, and capture file merging.

Enables Alexa+ to answer plain-English questions about a home network using live diagnostics such as ping latency, bandwidth, connected devices, and interface health, with optional local or AWS Bedrock LLM reasoning and safe service restart tools.

Provides a read-only summary of Ubuntu server status including system version, resource usage, apt updates, service health, security logs, and hardware information to AI clients via MCP tools.

A read-only MCP service for production troubleshooting that lets you register database, log, code, and message-queue connections in a web console, then have AI clients query them safely by target name. Models never supply hosts, accounts, or passwords themselves, and all operations are restricted to a read-only whitelist with audit logging.

Enables MCP clients such as Claude to check current uptime status, inspect monitors and incidents, trigger fresh checks, and retrieve status summaries from a self-hosted monitoring service.

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.