⚙️ AI Workflows
Ready-to-use automation templates combining AI agents and MCP servers. Step-by-step guides to build powerful AI pipelines.
10 Workflow Templates
Automated Code Review with AI Agents & MCP Servers
Build an automated code review pipeline using AI coding agents and MCP servers for GitHub pull requests. Integrates Cursor, Claude, and Git MCP servers.
AI-Powered Customer Support Automation Workflow
Create an intelligent customer support system that automatically routes, responds to, and escalates support tickets using AI agents and knowledge base MCP servers.
AI Research Paper Analysis & Summarization Pipeline
Automate research paper discovery, analysis, and summarization using ArXiv MCP servers and AI agents. Perfect for researchers and R&D teams.
Automated Data Pipeline with Database MCP Servers
Build an end-to-end data pipeline that extracts, transforms, and loads data using AI agents connected to database and file system MCP servers.
Multi-Agent Content Creation & Publishing Workflow
Orchestrate multiple AI agents to research, write, edit, and publish content across platforms using MCP servers for social media and CMS integration.
AI Security Monitoring & Incident Response Workflow
Build an automated security monitoring system that detects threats, analyzes vulnerabilities, and orchestrates incident response using security-focused MCP servers.
RAG Knowledge Base Chatbot with MCP Servers
Build a production-ready RAG chatbot that answers questions from your documentation using vector search MCP servers and AI agents.
DevOps Infrastructure Automation with AI Agents
Automate infrastructure management, deployment, and monitoring using AI agents connected to cloud and DevOps MCP servers.
Web Scraping & Data Enrichment Pipeline
Build an intelligent web scraping pipeline that extracts, enriches, and structures data from multiple sources using AI agents and web scraping MCP servers.
Personal Productivity AI Assistant Workflow
Create a personal AI assistant that manages your calendar, emails, notes, and tasks by connecting productivity MCP servers into a unified workflow.