"An introduction to programming in Golang" matching MCP servers:

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

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

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

MCP servers for real-time development monitoring and interactive pair programming.

Aggregates logs from multiple processes and provides an MCP server for AI agents to access, search, and manage logs in real-time.

Laravel Telescope-style debugging for Hono apps whose dashboard endpoint is also an MCP server: read recent exceptions with the request that produced them, recent requests filtered by status or duration, one request in full, and the slowest queries. Five read-only tools, zero runtime dependencies.

An MCP server that gives coding agents programmatic access to Sumo Logic logs via the Search Job API, enabling issue triage in preview deployments and production without leaving the editor.

A drop-in Model Context Protocol (MCP) server that lets an AI agent query PostgreSQL — read-only, enforced at the database level, with real SQL validation, timeouts, cost limits, OAuth 2.1, and an audit trail.

An MCP server for Dead Man's Snitch that enables AI assistants to manage monitoring snitches, including creating, updating, checking in, and pausing monitors for scheduled tasks and cron jobs.

An instrumented MCP server for debugging lost tool calls in Claude Desktop, using ping, echo, sized_echo, and slow_echo tools to record and analyze the full protocol flow.

MCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.

Connects MCP-capable AI clients to a monitoring API to inspect cron and recurring-task checks, with opt-in mutations for pings, integrations, and check changes.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

Enables Claude Code to inspect network traffic, query the DOM, read console logs, and capture WebSocket frames in Firefox.

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

Fast and minimal Sentry MCP server written in Rust

An MCP server that emits OpenTelemetry traces, metrics, and logs to OTLP endpoints in various formats. It includes tool-mimicry profiles to generate realistic traffic resembling common tools like nginx, postgres, and AWS Lambda for testing and demonstration purposes.

An MCP server that monitors and provides analytics on weekly report submissions in a Google Sheet, allowing users to check missing submissions, view statistics, and track individual reporting status.

A server that enables AI assistants to access and query Grafana dashboards, metrics, logs, and configurations through an MCP protocol interface.

An AI-powered server that provides rapid debugging of server logs with actionable fixes in under 30 seconds, featuring real-time monitoring and root cause analysis through Google Gemini integration.