"How to add documentation to a project or system" matching MCP servers:

Read-only MCP server for observing Linux hosts (systemd, ZFS, Docker, VMs, network, hardware, NixOS) as a graph of objects with provenance. Provides seven tools to list hosts, get status, collections, objects, evidence, lookup, and changes.

Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

rhizome-mcp is a local-first MCP server for task tracking and coordination of autonomous AI coding agents, providing crash-safe issue claiming, durable project memory, and dependency graphs using SQLite. It enables agents from different MCP-compatible clients to share a consistent view of project work with no accounts, Docker, or network dependency.

Provides access to your VictoriaTraces instance and seamless integration with VictoriaTraces APIs and documentation for querying traces, services, and operations.

This project implements a simple MCP server in Go that exposes a single tool (create_short_link) to generate short URLs using the Rebrandly API.

Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.

Enables interaction with Bitbucket through the Model Context Protocol, allowing users to manage pull requests, add comments, review code, create tasks, and perform other repository operations using natural language.

An MCP (Model Context Protocol) server for managing Tailscale resources using the official Tailscale Go client library v2. This server provides complete coverage of the Tailscale API with enhanced, self-descriptive tools powered by OpenAPI documentation.

Local, open-source multi-account MCP broker — one endpoint, every account. Add credentials once and switch identity without reconnecting, from any LLM client.

Enables AI assistants to control Pi-hole DNS filtering, including domain management, query analysis, and system administration, with support for multiple Pi-hole instances and synchronization.

Simple MCP Runner makes it effortless to safely expose system commands to language models via a lightweight MCP server—all configurable with a clean, minimal YAML file and zero boilerplate.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

Use Tavily Search to search for news pages or images.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Connect any AI client to the CaBrain memory system via MCP, exposing tools for memory recall, retain, and brain management.

MCP server that exposes live host metrics (CPU, memory, processes, network) to Cursor/Claude via /proc and optional eBPF, enabling system monitoring dashboards and natural language queries.

ZCP is a CLI with Zerops MCP that makes your agent a Zerops power-user. It runs either inside your project, or is connected through zCLI's VPN functionality to the project from your terminal. Your agent. Your subscription. Your code. Your infrastructure. Your IDE.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

A powerful and flexible Kubernetes MCP server implementation with support for OpenShift.