Complete Guide to Making Money with MCPs

Key Concepts

MCPS (Machine-Centric ProtocolS), AI Agents, Monetization, Stripe Integration, Authentication, Usage-Based Pricing, Subscription Model, Go-to-Market Strategy, Cloudflare, Serverless Development, Prompt Engineering, API Integration, Business Process Automation.

MCPS: A Massive Opportunity

The video emphasizes that MCPS represents a significant opportunity for monetization, contrasting it with the current landscape where many build valuable MCP servers without direct financial gain. The core idea is to enable AI agents to access and utilize tools and services through a standardized protocol, creating a new market for AI-driven applications.

Key Points:

• MCPS as a Standard: MCPS is presented not just as a protocol but as an emerging standard for connecting AI agents to tools, fostering collaboration and tool sharing among developers.
• LLMs and Natural Interaction: The rise of LLMs allows for more natural interaction with technology, enabling backend-focused product development that connects to AI agents via MCPS.
• Scalable Distribution: MCPS facilitates wider distribution by allowing AI agents to use tools like CRMs without human intervention, increasing scalability.
• Early Stage Advantage: The video highlights the current lack of monetization in the MCPS space, drawing a parallel to the early days of the Open API protocol, where developers profited by distributing APIs.
• Platform Support: Major platforms like Anthropic, Cursor, Windsurf, OpenAI, and Windows already support MCPS, expanding its potential reach.

Success Stories and Business Ideas

The video explores existing success stories and proposes new business ideas centered around MCPS.

Examples:

• 21st.deaf Magic AI Agent: This agent achieved $400K MRR using MCPS to build web applications directly from IDEs like Cursor or Windsurf.
• Magic UI: This platform allows agents to fetch pre-built UI components.
• Platform Integrations: Many platforms are implementing MCP servers for existing products (e.g., Notion, GitHub, Reddit).

Business Ideas:

1. Improve My Prompt MCP: An MCP that refines user prompts using another LLM and a specialized prompt. This is the MCP that is built in the tutorial.
2. Proprietary Data MCPS: MCPS based on unique data sources, such as Context 7, which scraped documentation for coding platforms. Examples include combining legal data, lead sourcing data (e.g., Apollo), and trading data.
3. Business Process MCPS: MCPS designed to automate specific business processes, such as reposting content across social media platforms (TikTok, YouTube, Twitter) with added functionalities like scheduling.
4. Windows MCP: Leveraging Windows' MCP server to create agents that automate tasks on applications like Word or Excel.
5. Internal MCPS: MCPS tailored for specific industries, generating revenue through setup or licensing fees.

Idea Reality Check

Before building an MCP, the video suggests evaluating the idea based on three key questions:

1. Specialized Knowledge or Data: Does the MCP leverage unique APIs or data that are difficult to replicate?
2. Repeated Use and Problem Solving: Will users (or agents) repeatedly use the MCP to solve a specific problem?
3. Habit Formation: Does the MCP encourage habitual use by AI agents?

Pricing Models

The video outlines various pricing models for monetizing MCPS:

1. Usage-Based: Charging per request or token consumption, common in API marketplaces.
2. Subscription: Charging a monthly fee for access to the MCP.
3. Affiliate/Referral: Earning commissions on purchases made through the MCP, such as with an Amazon product search MCP.
4. Licensing: Charging a one-time setup or licensing fee, suitable for internal MCPS.

Tips and Tricks for Building and Monetizing

The video provides actionable tips for building and monetizing MCP servers:

1. Focus on One Use Case: Start with a Minimum Viable Product (MVP) that solves a specific problem.
2. Collect Email Addresses: Gather emails for reactivation campaigns, as demonstrated in the tutorial's authentication process.
3. Offer a Free Tier: Provide a free tier to allow users (agents) to evaluate the server's quality.
4. Great Documentation: Create comprehensive documentation with examples to facilitate developer adoption.
5. Feedback Tool: Implement a tool within the MCP to collect user or agent feedback for analysis and improvement.
6. Build in Public: Share the development process publicly to gain traction and feedback.

Go-to-Market Playbook

The video presents a step-by-step go-to-market strategy:

1. Create an MCP: Develop an MCP that addresses a specific problem.
2. Offer a Free Trial: Provide a free trial, such as five free requests.
3. Charge for Increased Usage: Implement a subscription model (e.g., $20/month) for higher usage.
4. Market on Communities: Promote the MCP on platforms like GitHub, Discord, Reddit, and marketplaces like mcp.so.
5. Document the Experience: Share the development journey on social media.
6. Listen to Feedback: Gather and incorporate user feedback.
7. Ship Updates: Regularly release updates and notify users via email.

Tutorial: Creating an MCP Server with Stripe Payments and Authentication

The video includes a tutorial on building an MCP server with Stripe integration and authentication using a boilerplate repository created by Ian.

Steps:

1. Clone the Repository: Clone the MCP boilerplate repository from GitHub.
2. Cloudflare Account: Create a Cloudflare account, which is required for the tutorial.
3. Stripe Account: Set up a Stripe account (using a test mode if necessary). Stripe Atlas is mentioned as a service to create a US entity for Stripe access.
4. Install Dependencies: Run npm install to install required packages and install Cloudflare's Wrangler tool.
5. Cloudflare Database: Create a new database in Cloudflare for user login and add the output to the wrangler.json file.
6. Environment Configuration: Copy the environment file and create a Google Cloud project for OAuth credentials.
7. Google Cloud Credentials: Create OAuth client ID credentials in Google Cloud, specifying the authorized redirect URI as localhost:8787/callback/google. Download the JSON secret key.
8. Stripe Configuration: Create a Stripe sandbox account and create a product with both recurring monthly pricing and usage-based pricing (per request). Configure a meter in Stripe to track usage.
9. Billing Portal: Configure a billing portal in Stripe to allow customers to manage their subscriptions.
10. Environment Variables: Add the client ID, client secret, Stripe price ID, product ID, and a cookie encryption key to the environment variables.
11. Testing: Run npx wrangler dev to start the local development server and add the MCP server to Cursor.
12. Tool Creation: Use Cursor's rules file to create a new tool (optimize prompt) with specified parameters (unedited prompt, level of detail, target AI platform).
13. Subscription Testing: Test the tool in Cursor, which should prompt for a Stripe subscription payment. Use Stripe test cards to activate the subscription.

Conclusion

The video provides a comprehensive guide to understanding and monetizing MCPS. It emphasizes the importance of focusing on specific use cases, leveraging unique data or APIs, and implementing effective pricing and marketing strategies. The tutorial offers a practical demonstration of building an MCP server with Stripe integration and authentication, enabling developers to create and monetize AI-driven tools and services. The key takeaway is that MCPS represents a significant opportunity for building the next generation of SaaS products that are directly integrated with AI agents.