laravel/boost
Laravel-focused MCP server for augmenting your AI powered local development experience.
What it solves
Laravel Boost helps developers avoid the common pitfalls of AI-assisted coding by providing the specific context and structure required for AI tools to generate high-quality, Laravel-specific code.
How it works
It provides the essential context and structure that AI models need to understand the Laravel framework's patterns and requirements to generate accurate code snippets and applications.
Who it’s for
Developers using the Laravel framework who want to improve the accuracy and quality of the code generated by AI assistants.
Highlights
- Accelerates AI-assisted development
- Focuses on Laravel-specific code generation
- Provides essential context for AI tools
Related
- Project
ratel-ai/ratelRatel is a Rust‑backed retrieval engine with TypeScript and Python SDKs that lets LLM agents load only the tools and skill playbooks they actually need for each turn, cutting token cost and improving accuracy. It works with any model, requires no vector DB, and provides adapters for popular agent frameworks.
- Project
NeoLabHQ/context-engineering-kitA plug‑in marketplace for LLM‑based coding assistants (Claude Code, Gemini, Antigravity, etc.) that supplies token‑efficient, context‑engineering patterns—reflection loops, sub‑agent judges, specification‑first development, code‑review agents, and Git helpers—to make AI‑generated code more reliable and easier to integrate into CI pipelines.
- Project
MaestroError/LarAgentAn AI agent development framework for Laravel that allows developers to create and maintain AI agents using an Eloquent-like API and Laravel-style tooling.
- Project
jfrog/boostBoost is a local‑first tool that filters and compresses the noisy output (terminal logs, build reports, large JSON responses, files) that AI coding assistants read. By removing banners, progress bars, and other irrelevant text, it cuts the number of tokens sent to the LLM, saving cost and speeding up inference. It works with popular agents (Claude Code, Copilot, Cursor, etc.) via a desktop app or CLI, offers a dashboard, OpenTelemetry export, and can be used in CI pipelines.
- Project
upstash/context7A platform that provides AI coding agents with up-to-date, version-specific library documentation and code examples to prevent hallucinations and outdated code generation.