Co-authored with Claude Code, the workflows-mcp project focuses on building powerful Model Context Protocol (MCP) implementations to enable Language Model Models (LLMs) to execute complex, multi-step workflows seamlessly. By providing structured, reusable workflows that combine tool usage with cognitive reasoning, workflows-mcp revolutionizes how AI assistants handle complex tasks. Key features include structured workflows with step-by-step instructions, cognitive actions for advanced reasoning, advanced control flow with branching and loops, state management for tracking variables, comprehensive validation, and execution tracking for monitoring success rates. The project also offers type-safe TypeScript support, dependency management for control over variable visibility, and performance optimization through differential updates and progressive step loading. Installation is made easy with npx or npm, while configuration can be done in Claude Desktop or through global installs. The project structure revolves around JSON documents defining steps for an LLM to execute, with various action types such as tool actions and cognitive actions like analyze, consider, research, and validate. Workflows-mcp aims to empower developers and AI assistants with the tools necessary to streamline and enhance their workflow processes for more efficient and effective task execution.
