I built next gen AI Agents with MCP + Claude (STEAL my workflow)

Key Concepts

• MCP (Model-as-Control-Program): Agents with tools, allowing AI models to interact with external resources and perform complex tasks.
• AI Agents: Models using tools in a loop, capable of iterative problem-solving and task execution.
• N8N: A workflow automation platform similar to Zapier, enabling the creation of AI agent nodes.
• Docker: A platform used to containerize applications, including MCP toolkits for Claude.
• Glyph: A workflow builder that allows users to create and remix workflows, enabling AI agents to perform specific tasks.
• Claude Artifacts: A feature in Claude that allows users to render and share AI-generated content.
• System Prompt: Instructions given to an AI model to guide its behavior and define its role.

1. Introduction to MCPs and AI Agents

• The video introduces the concept of using MCPs within LLMs like Claude to enhance their capabilities.
• MCPs are framed as "agents with tools," emphasizing the ability of AI models to interact with external resources.
• The increasing interest in AI agent builders is highlighted, with Claude Sonnet 4 and Claude Opus 4 cited as examples of agents out of the box.
• The core idea is giving AI agents access to tools to significantly improve workflows.

2. The Significance of Tools for AI Agents

• Tools provide AI agents with context and capabilities they wouldn't otherwise have.
• Example: Perplexity built a billion-dollar company by adding a search tool to its AI model.
• Example: Cursor, an AI code editor, uses tools to search the code base and the internet for documentation.
• Boring Marketer uses MCPs and N8N workflows to equip AI agents with marketing-related tools.
• Sam Altman's statement about the "era of the idea guy" is mentioned, emphasizing the importance of identifying valuable applications for AI.

3. Using Docker for MCP Toolkit

• Docker is presented as a platform for easily adding tools to Claude through its MCP toolkit.
• The MCP toolkit provides access to a catalog of tools, similar to Zapier integrations.
• Example: Firecrawl, a tool for searching the internet, is mentioned, but its complex configuration is noted as a current limitation.
• The need for a unified platform to manage API keys for various tools is identified as a startup opportunity.

4. Favorite Tools: Notion and Glyph

• Notion and Glyph are highlighted as two favorite tools for use with MCPs.
• Notion: Allows AI agents to read and write content, add comments, and perform other tasks within a Notion workspace.
• Glyph: Enables the creation of AI employees through customizable workflows.

5. Practical Demonstration: Using Notion with Claude

• A step-by-step demonstration is provided on how to use Notion with Claude through Docker's MCP toolkit.
• The process involves enabling the Notion tool in Docker, obtaining an integration token from Notion, and configuring Claude to access the Notion workspace.
• Example: The AI agent is instructed to find short-form hooks in a Notion database and write content about DIA Browser.
• The AI agent successfully retrieves information from the Notion database and generates content based on the provided examples.
• The ability to add the generated content as separate entries in the Notion database is also demonstrated.

6. Claude Artifacts vs. MCP

• The discussion explores the differences between Claude Artifacts and MCP.
• Claude Artifacts allow users to render and share AI-generated content within the Claude interface.
• MCP, on the other hand, enables AI agents to interact with external tools and resources, such as Notion and Glyph.
• The potential for combining Claude Artifacts with MCP is discussed, such as using MCP to scrape Reddit for information and render it as a mermaid diagram in Claude Artifacts.

7. Using Glyph for AI Workflows

• Glyph is presented as an easy-to-use workflow builder that allows users to create and remix workflows.
• Example: A workflow is created to fix the ratio of an image.
• The integration of Glyph with Claude is demonstrated, allowing users to run Glyph workflows directly from the Claude chat interface.
• Example: The AI agent is instructed to use a Glyph workflow to generate thumbnails for a video on using Docker for MCP.
• The AI agent successfully runs the Glyph workflow and generates five different thumbnails.

8. The Importance of Examples

• The importance of providing AI agents with good examples is emphasized.
• Example: The thumbnail ideator workflow uses a PDF containing examples of successful thumbnails to guide the AI agent's output.
• The idea of collecting and curating examples is presented as a potential business opportunity.

9. Creating Custom Projects in Claude

• The video explains how to create custom projects in Claude to define the AI agent's role and behavior.
• Example: A project is created called "VibeCode CEO," which instructs the AI agent to act as the CEO of the content team and use Notion as its primary tool.
• The use of double brackets to trigger specific actions, such as generating thumbnails using Glyph, is also demonstrated.

10. Practical Tips for Setting Up MCP

• Practical tips are provided for setting up MCP, including how to obtain the Notion integration token and configure access permissions.
• The importance of restarting the Docker server after making changes to the MCP tools is emphasized.

11. Conclusion: The Future of AI Agents with Tools

• The video concludes by acknowledging the current jankiness of the MCP setup process but emphasizing its potential.
• The importance of experimenting with these tools and understanding their capabilities is highlighted.
• The speaker expresses confidence that the process will become much easier in the future, potentially through direct integration into platforms like Claude.
• The potential for Claude to gain market share by being the first to offer seamless integration of external tools is discussed.
• A brief overview of Vibe Code App, a mobile app builder, is provided.

Key Takeaways

• MCPs (agents with tools) significantly enhance the capabilities of LLMs like Claude.
• Docker provides a platform for easily adding tools to Claude through its MCP toolkit.
• Notion and Glyph are valuable tools for use with MCPs, enabling AI agents to interact with external resources and perform complex tasks.
• Providing AI agents with good examples is crucial for achieving desired outputs.
• Creating custom projects in Claude allows users to define the AI agent's role and behavior.
• While the current MCP setup process is janky, its potential is undeniable, and it is likely to become much easier in the future.