"An introduction to the Laravel PHP framework" matching MCP servers:

An MCP server providing automated workflows, rules, and actionable tools for implementing full multilingual localization in Laravel applications.

An MCP server providing standardized local environment configuration, scaffolding, and validation workflows for Laravel projects.

A collection of Laravel helper tools for integration with Cursor IDE, providing features like log viewing, error searching, artisan command execution, and model information display directly within the editor.

Enables secure execution of Laravel Artisan commands through AI assistants, allowing controlled management of Laravel projects via natural language.

Enables AI assistants to introspect a Laravel application's routes, models, controllers, migrations, and more through the Model Context Protocol, running locally via php artisan commands and filesystem scanning.

A starter template for building Model Context Protocol (MCP) servers with mcp-framework. It includes an example tool and CLI for adding more tools.

Enables AI coding agents to run one-shot commands and copy single files to and from remote servers through The Bastion, which authenticates, authorizes, and records each action. Access is controlled by the bastion rather than allowlists or deny lists.

Exposes Laravel development tools (artisan, migrations, config, schema, logs) as MCP tools for use with compatible clients.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

Enables AI assistants to diagnose, troubleshoot, and manage PC settings on Windows, macOS, and Linux through natural language commands.

An MCP server that lets Claude query Google's Gemini CLI as a sub-agent. Get second opinions, verify information, and cross-reference answers between AI models.

Enables AI agents to manage a Canonical Landscape estate, including inventory, alerts, patching, and script execution, with built-in safety layers to prevent accidental destructive actions.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Enables cloud agents to securely operate local machine resources (files, commands, screenshots) via standard MCP protocol.

A framework for building Model Context Protocol (MCP) servers using pure Bash scripts, allowing for the creation of tools, resources, and prompts without Node.js or Python runtimes. It provides a complete implementation of the MCP spec compatible with any environment running Bash 3.2+ and jq.

Wraps Kali Linux penetration testing tools for authorized security assessments, driven by a local LLM via LM Studio.

Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

Enables authenticated remote MCP clients to manage a Kali Linux environment, run modular tools in sandboxed or optional host contexts, configure networking, and monitor jobs through a live WebUI.

Automates Ansys Fluent simulation workflows, enabling environment checks, case execution, UDF management, and result export through MCP tools.

A single-purpose MCP server that lets an AI assistant run commands over SSH on a fixed, pre-configured host only, with an explicit per-call confirmation gate before execution.

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

An MCP server that gives coding agents hands and eyes on an Android device, providing 19 tools for building, testing, installing, UI inspection, input, logs, and toolchain diagnosis. It returns concise, structured results to make the build-debug loop efficient.

Exposes the official lark-cli as an MCP server, enabling agents to execute arbitrary CLI commands, query API schemas, and manage authentication.

Lets an AI assistant look after Android TV boxes, phones and watches over ADB: find devices on the network, see the screen, tap and type, install apps. Package changes are dry-run first, with a protected set read off the device and one-call rollback.

An MCP server that lets AI agents see, act on, and verify the rendered Neovim UI, like a Playwright for Neovim. It provides tools to launch/attach to Neovim, observe the screen, send input, and wait for conditions.

An MCP server for creating, validating, and formatting Git commits with emojis following the conventional commit standard.

An MCP server that lets an AI agent use a real terminal the way a person does: type, press keys, click, read the screen, take a screenshot.