"A guide to coding a monorepo" matching MCP servers:

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

Enables natural language queries of the Chrome UX Report API to fetch Core Web Vitals (LCP, INP, CLS, FCP, TTFB), compare form factors, benchmark pages against site averages, and analyze up to 40 weeks of performance trends.

Enables querying Margint per-customer AI margins and costs from MCP clients. Provides tools to list customers, drill into costs, check budgets, and view workspace-wide cost breakdowns.

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.

ac-infinity-mcp is an MCP server that connects Claude (and other AI assistants) directly to your AC Infinity controllers — so you can read live sensor data, run analytics, and adjust fan speeds or port states using natural language, without opening the AC Infinity app.

Enables SEO audits and URL monitoring via the SEO Radar API from any MCP-compatible AI client.

A read-only MCP server that exposes AI Disk Doctor Core's scan, model inventory, and history tools via local stdio, with no mutation or shell capabilities.

Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.

A read-only MCP server for querying AI provider administration APIs, providing normalized usage, cost, and dashboard data for OpenAI and Anthropic.

AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.

A simple MCP server providing ping, echo, and TCP host health-check tools with latency measurement. It enables transport testing and real network connectivity checks through natural language.

MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.

Track brand visibility across ChatGPT, Perplexity, Claude, and Gemini.

Provides AI-aware failover for Mihomo proxy on macOS by validating real OpenAI paths and switching proxy groups after verified hard failures. It offers a local stdio MCP server for diagnostics, status, and safe management of the AI proxy group.

Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.

Zero-config MCP server that gives AI coding assistants a real-time diagnostic snapshot of your local dev environment. Detects framework, running services, recent errors, git state, and provides a health diagnosis in one call.

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

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

Estimates the environmental footprint of your AI use — energy (kWh), miles driven, water used for cooling, and CO₂ — plus a prompt-efficiency score, working with any AI client by measuring token usage.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9