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Laravel MCP Companion

MCP Server

Centralized, offline-ready documentation hub for Laravel and its ecosystem

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Updated 11 days ago

About

Laravel MCP Companion aggregates and indexes high-quality Laravel core, service, and community package documentation across multiple versions (6.x‑latest). It provides instant, offline retrieval with Laravel-specific search and auto-discovery of new docs for AI assistants.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Laravel MCP Companion – A Dedicated Documentation Hub for Laravel Developers

Laravel MCP Companion is an offline‑first Model Context Protocol server that aggregates, indexes, and serves the entire Laravel ecosystem’s documentation. Instead of generating new content, it pulls existing high‑quality resources from the official Laravel site, service documentation (Forge, Vapor, Nova, Envoyer), and popular community packages (Spatie, Livewire, Inertia, Filament). The server then exposes these resources through MCP’s standardized API, allowing AI assistants such as Claude to query and retrieve precise answers with zero external network traffic.

The core problem it solves is the fragmentation of Laravel knowledge. Developers routinely jump between multiple websites—Laravel’s core docs, service‑specific guides, and third‑party package readmes—to find the right snippet. This creates latency, increases token usage for AI assistants, and can lead to outdated or inconsistent information. By consolidating all relevant material into a single searchable index, Laravel MCP Companion delivers instant, version‑aware answers while keeping the AI’s context window lean.

Key capabilities include:

  • Multi‑version support (6.x – latest): Search across any Laravel release, ensuring backward compatibility for legacy projects.
  • Auto‑discovery of service docs: New sections in Forge, Vapor, Nova, or Envoyer are detected daily and indexed automatically.
  • Community package coverage: Pre‑processed markdown from widely used packages reduces token consumption and speeds up retrieval.
  • Offline operation: Once the index is built, no external HTTP requests are made during queries, guaranteeing consistent performance and privacy.
  • Laravel‑specific search: Contextual relevance scoring prioritizes core framework concepts over generic documentation, improving answer quality.

Real‑world scenarios where this server shines include:

  1. Rapid prototyping – A developer can ask an AI assistant, “How do I set up a scheduled task in Laravel 9?” and receive the exact code snippet from the official docs without any internet lookup.
  2. Legacy maintenance – Teams maintaining older Laravel 6.x applications can query the same server for backward‑compatible guidance, avoiding confusion between version differences.
  3. Package integration – When adding a new package like Livewire, an AI can instantly provide the installation steps and integration patterns from the package’s own readme.
  4. Team knowledge sharing – The server can be deployed internally, ensuring that all team members—whether on‑premise or remote—access the same curated documentation set.

Integration into AI workflows is straightforward: an MCP‑compatible assistant sends a search request to the server’s endpoint, receives structured results (title, snippet, URL), and can optionally fetch the full content via . Because the data is locally cached, response times are sub‑second and token usage is minimized. The server’s daily auto‑discovery loop guarantees that new documentation is reflected automatically, eliminating manual updates.

Unique advantages stem from its offline-first design and Laravel‑centric focus. While general MCP servers may provide generic documentation, Laravel MCP Companion offers a depth of detail—version‑specific nuances, service integration guides, and curated package recommendations—that is hard to match elsewhere. For Laravel teams looking to embed AI assistance directly into their development environment, this server delivers a seamless, high‑performance knowledge layer that keeps developers productive and codebases consistent.