Those MCP totally 10x my Cursor workflow…

Key Concepts

mCP (Modo Context Protocol), AI coding IDE integration, Cursor, Entropic, AI agents, data sources, external systems, USBC analogy, chat co-pilot, composer, planning, actions, prompts, external resources, API endpoints, mCP Marketplace, sequential thinking, Reddit mCP, browser tools, Chrome extension, console logs, network tabs, debugging, guest L Elements, text-to-image model, gaming assets, custom mCP server, Cloudflare Workers, serverless functions, replicate API, AI Builder Club Community.

mCP: A Universal Interface for AI Coding

The video introduces mCP (Modo Context Protocol), a universal interface developed by Entropic that allows AI agents to connect to various data sources and external systems. It's likened to a USBC port for AI applications, providing a standardized way to integrate AI models with different resources.

Evolution of AI Coding

AI coding has evolved from simple chat co-pilots to sophisticated composers and agents capable of planning and executing diverse actions. While tools like Cursor offer default actions, mCP enables users to extend these capabilities by building custom integrations.

mCP Use Cases

mCPs can be used for various purposes:

• Prompt Engineering: Guiding agent behavior with specific prompts.
• External Resource Access: Connecting to external resources and APIs.

Navigating the mCP Marketplace

Several mCP marketplaces exist, such as gl.as, SMI, and Cursor.directory, where users can find and utilize mCPs created by others.

Installing and Using Existing mCPs

The process involves searching for desired mCPs (e.g., sequential thinking, Reddit mCP) and adding them to the AI coding IDE (e.g., Cursor).

Steps:

1. Copy the provided command line.
2. In Cursor, navigate to settings, features, and mCP server.
3. Add a new mCP, specifying a name and type (usually "command").
4. Paste the command line and add the mCP.

Example: Adding a sequential thinking mCP forces the agent to plan through multiple steps.

Challenges:

• Lack of standardization in installation and setup.
• Inconsistent quality and functionality of available mCPs.

Featured mCPs and Their Applications

The video highlights several useful mCPs that enhance productivity.

Browser Tools mCP

This mCP grants Cursor access to the browser's console logs and network tabs, facilitating easier debugging and communication with the IDE.

Installation:

1. Clone the Chrome plugin from the provided GitHub repository.
2. Load the unpacked extension in Chrome's developer mode.
3. Add the mCP server in Cursor, specifying the command line.
4. Run the browser tools mCP server using the command MPX @agents/browser-tools-server.

Functionality:

• Retrieving console logs and network errors.
• Selecting elements on the webpage using "guest L Elements."
• Updating element styles based on prompts.

Example: Updating the style of a selected element to resemble a "pocket car."

Custom mCP for Image Generation

The video demonstrates creating a custom mCP server to connect Cursor to a text-to-image model for generating gaming assets.

Process:

1. Take a screenshot of the game.
2. Prompt Cursor to generate images of dogs for cards instead of emojis.
3. The mCP calls the image generation function and returns the generated images.

Example: Generating unique dog images for a memory game.

Building Your Own mCP Server with Cloudflare Workers

The video provides a step-by-step guide to setting up a custom mCP server using Cloudflare Workers.

Steps:

1. Create a new Cloudflare project using the command mpm create Cloud flare @latest.
2. Choose the "Hello World" worker example and TypeScript as the language.
3. Navigate to the project directory and run mpm install.
4. Modify the index.ts file to define custom functions.
5. Activate the mCP in Cursor by adding a new mCP with the appropriate command line.

Example: Creating a "say hello" function that returns a predefined message.

Integrating with Replicate API for Image Generation

The video demonstrates integrating with the Replicate API to generate images.

Steps:

1. Write a new function in index.ts that calls the Replicate API.
2. Include the API key directly in the file (not recommended for production).
3. Deploy the worker using npm run deploy.
4. Test the function in Cursor by providing a prompt.

Example: Generating an image of a "dog Val AI" using the Replicate API.

Conclusion

mCPs offer a powerful way to extend the capabilities of AI coding IDEs like Cursor by connecting them to various data sources and external systems. While the current mCP marketplace has challenges in terms of standardization and reliability, building custom mCP servers using tools like Cloudflare Workers provides a flexible solution. The video encourages viewers to explore the possibilities of mCPs and join the AI Builder Club Community for curated lists of useful mCPs.