"Buy Me A Coffee" matching MCP servers:

A read-only IBM MQ diagnostic MCP server that safely provides AI agents with typed root-cause analysis and verified IBM documentation, while incorporating prompt-injection defense, OIDC+RBAC, and tamper-evident audit.

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.

Model Context Protocol server for Verlon AI that exposes gates, logs, recommendations, and experiments as MCP tools, enabling coding agents to inspect and manage AI infrastructure natively.

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.

An MCP server that enables AI assistants to interact with Tenzir, a data pipeline engine for security operations, including executing pipeline queries, managing OCSF schemas, and generating parsers.

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.

Enables observability and governance for local LLMs via Ollama, including auditing model usage, scanning prompts for secrets/PII, and enforcing allow/deny policies.

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.

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

Provides a standardized MCP interface for querying Graylog logs, enabling AI agents to search, diagnose, and correlate runtime logs with code via configurable profiles.

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.

A Model Context Protocol server that enables retrieving and analyzing Sentry issues, including stacktraces and debugging information.

MCP server for Minecraft modpack diagnostics, enabling mod conflict detection, log/crash analysis, and dependency lookup via Modrinth.

A read-only MCP server for Linux system monitoring and OS algorithm simulation, exposing tools for memory, filesystem, process, and CPU scheduling observations.

Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.

Perimeter security for your AI Infrastructure.

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.

Evidence-first MCP server for diagnosing problems with hooks, plugins, skills and configuration, returning ranked probable causes and reviewable fixes without modifying the workspace.