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I started working on a MCP server for Laravel Herd and damn, this is like a glimpse into the future 🔥 For example, in Cursor I can just say: "I want to search my models via Typesense" This checks Herd if Typesense is installed, installs it if needed and...

22,218 просмотров • 1 год назад •via X (Twitter)

Комментарии: 11

Фото профиля Marcel Pociot 🧪
Marcel Pociot 🧪1 год назад

Or you could say "Apply the correct configuration from my local mariadb service"

Фото профиля Marcel Pociot 🧪
Marcel Pociot 🧪1 год назад

The combination of a development tool with an MCP server is absolutely blowing my mind. It unlocks so many possibilities! The important part is that the user doesn't need to know which tools the MCP provides - the AI agent can just decide on its own which tools should be called

Фото профиля Manticore Search
Manticore Search1 год назад

🚀 Star Manticore Search on #GitHub today and join our quest for the ultimate search solution!

Фото профиля Jordan Dalton
Jordan Dalton1 год назад

@laravelphp MCP servers are amazing…especially when chaining tool calls across different MCPs.

Фото профиля Marcel Pociot 🧪
Marcel Pociot 🧪1 год назад

@laravelphp This is me the entire day The combination of MCP + Herd is absolutely insane

Фото профиля Patricio
Patricio1 год назад

@laravelphp MCP is insane! Function call was already, but the standard will enable so many things!!

Фото профиля Jim Hull
Jim Hull1 год назад

@laravelphp So great you’re doing this now…and more importantly, how you’re explaining it. Was trying to figure out difference between APIs and MCP, you’re really just exposing tools right?

Фото профиля Marcel Pociot 🧪
Marcel Pociot 🧪1 год назад

@laravelphp Yes exactly. The MCP server just exposes different tools and the client decides which ones it should use

Фото профиля Ludo Esmanne
Ludo Esmanne1 год назад

@laravelphp Amazing, I want this to try! 😬

Фото профиля Fady G Andrawes
Fady G Andrawes1 год назад

@laravelphp mind blowing 💣💣

Фото профиля Ben 🤙🏼
Ben 🤙🏼1 год назад

@laravelphp Yes please!!!

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MCP is an absolute game-changer. (Together with DeepSeek, MCP is probably the hottest thing in AI over the last 6 months.) I use Cursor to write code 90% of the time. I built an MCP server to connect the Cursor agent to GroundX, an open-source RAG system, and I'm not going back. This is officially insane! Here is what I did, step by step: First, a little bit of context. I maintain an end-to-end Machine Learning System with several pipelines to process data, train, evaluate, register, deploy, and monitor a model. I've written a lot of documentation explaining how the system works and how to modify and maintain it. There's also the documentation of the few libraries I used to build the system. I'm a massive fan of GroundX, an open-source enterprise-grade RAG system you can run on your servers or deploy to any cloud provider. I've been working with them for a long time. GroundX offers two services. First, the "ingest" service uses a custom, pretrained vision model to ingest and understand your data. I used this to process all the documentation I have for my code. Markdown files, source code, HTML files, and even PDF documents. Everything I've written related to my project went into GroundX. Their second service is "search," which combines text and vector search with a fine-tuned re-ranker model to retrieve information from the data. I needed to connect Cursor with this service, and that's where MCP came in. I built an MCP server with two tools: 1. The first tool would go to GroundX and retrieve the available topics. Splitting the data into topics (or "buckets," as GroundX calls them) allows me to use the same setup to serve documentation from different topics. 2. The second tool would search GroundX under a specific topic for the context related to the supplied query. The magic happens after connecting the MCP server with Cursor. Now, I can ask any questions related to my project, and Cursor's AI agent retrieves the list of available topics from the RAG system and then searches it to provide relevant context to the model. I went from getting mediocre, sometimes wrong answers to 100% truthful, complete answers. Here is the crazy part:

Santiago

255,532 просмотров • 1 год назад