Workflows Directory for AI Agents
Ready-made workflows from our directory that combine MCP servers and AI skills into one continuous process, with provider and requirements per entry.
- Skill Road
- Workflows Directory for AI Agents
Workflows show more than a single tool. They describe a complete process: which steps belong together, which MCP server provides the data, which skill performs the analysis and where the usable result is created. That makes these entries a useful starting point when you want to structure a recurring task with AI agents without collecting every building block separately.
Skill Road documents workflows with requirements, involved components and provider context. This makes it easier to judge whether a process fits an existing Claude Code, ChatGPT, Cursor or automation environment. When a workflow depends on paid or external services, the detail page marks that context; the overview remains the neutral starting point for all published workflows.
Auditing and documenting cloud infrastructure
Combining the AWS MCP Server, Cloudflare API MCP Server, and Filesystem MCP: audit resources and configuration across two cloud providers and save the findings as a report.
Reproducing and fixing error reports
Combining Sentry MCP, GitHub MCP, and Playwright MCP: track down errors from monitoring, locate them in code, reproduce them in the browser, and fix them as a pull request.
Generative AI on Google Cloud
A Google developer and learning resource with Gemini notebooks, Google Cloud examples, RAG, grounding, and Agent Platform workflows.
Documenting research with source citations
Combining Fetch MCP, Context7, and Filesystem MCP: retrieve web content and current library docs, then save them locally as sourced notes.