I Automated My Entire Dev Workflow with AI (You Won't Believe How Easy It Is)

The author says repetitive work was taking time away from coding on UserJot, so they used MCP to let Claude interact with external tools and services. FastMCP is presented as a simpler way to build these servers, and the article shows tools for keyword research, support ticket summaries, task prioritization, and user feedback reading.

Reading notes

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• MCP lets AI assistants interact with files, APIs, terminal commands, databases, and other code-backed tools.
• FastMCP reduces boilerplate when setting up an MCP server.
• The keyword research tool pulls data from SEO APIs to return search volume, difficulty, and related keywords.
• The support ticket tool fetches recent tickets and summarizes them by category and priority.
• The task tool can list, add, complete, and prioritize development tasks, with prioritization based on impact and urgency.
• The UserJot tool reads feature requests from the API, sorted by votes and filtered by a minimum threshold.
• The current UserJot workflow is feedback submission, voting, reading top requests through the MCP tool, and using that data to decide what to build next.
• The setup steps are to install dependencies, create a server file, add it to Claude Desktop, and start using it.
• The reported results are about two hours saved per day, faster feature shipping, quicker support replies, and better decisions based on user data.
• The suggested starting point is one repetitive task that can be wrapped in a FastMCP server and connected to Claude.