"Kyverno policy examples and documentation" matching MCP servers:

A collection of Model Context Protocol implementations ranging from a minimal hello-world to an autonomous AI agent for software development.

GhostLink is a security-hardened MCP server that gives AI coding agents safe, deterministic access to local repositories through sandboxed, policy-gated tools for searching, reading, patching, and running curated commands.

Enables AI tools to interact with browsers for enhanced frontend development, providing context to LLMs through tools like API call analysis, screenshots, element selection, and documentation ingestion.

MCP server that provides AI coding agents automatic access to AGENTS.md documentation from GitHub repositories, enabling understanding of codebase conventions and patterns.

Provides read-only MCP tools for discovering UI libraries, recommending minimal compatible UI stacks, and auditing plans to enforce deterministic UI policy and quality gates for coding agents.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

Integrates with Dispersl to provide multi-agent orchestration for AI-driven software development, enabling code generation, testing, documentation, git operations, and chat.

An MCP server that implements a structured workflow for LLM-based coding, guiding development through feature clarification, documentation generation, phased implementation, and progress tracking.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

A policy layer between ChatGPT and the official Codex MCP server, adding safety controls like read-only sessions, approval policies, and secret scanning for secure daily use.

Provides AI coding agents with access to CleanSlice architecture documentation, rules, and conventions. It enables users to search documentation and retrieve essential patterns to help AI build applications correctly.

Classifies software implementation tasks using local Ollama models and recommends coding-agent models based on a deterministic policy.

A governed stdio bridge that lets DeepSeek Harness delegate scoped, resumable Codex tasks on the local machine with pinned sandbox and approval policy, read-back verification, and activity reporting.

Indexes GitHub repositories and provides living documentation context to coding agents, enabling them to ground work in actual repository conventions and propose doc updates.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

Enables MCP clients to asynchronously submit tasks to a persistent coding agent already running on a development machine, disconnect, and retrieve results later through a secure, policy-controlled gateway.

Server that enhances the capabilities of the Cline coding agent. It provides intelligent code suggestions, reduces hallucinations, and documents the knowledge base by leveraging your project's documentation and detecting the technologies used in your codebase.

An MCP server that exposes the Symbols/DOMQL v3 AI assistant capabilities to any MCP-compatible platform. Enables generating components, pages, projects, and more from natural language, as well as searching documentation and reviewing code.

Converts natural language specifications into working ladder logic and complete Studio 5000 projects, enabling AI-powered PLC programming with L5X and .ACD file generation, semantic search, and documentation access.