Workflows MCP

Workflows MCP (mcpn) is a lightweight server that turns collections of prompts and tool calls into reusable, version‑controlled AI workflows. It solves the problem of scattered “best practices” for interacting with external tools by providing a single, declarative language (YAML) to describe what the assistant should do and how it should orchestrate available MCP servers. Developers can therefore package complex sequences—such as generating a product requirements document, running unit tests, or debugging code—into a single workflow file that can be shared across teams and environments.

The server exposes several key capabilities. First, it lets you combine prompts with any number of MCP servers, creating a modular pipeline where each step can invoke tools like , , or custom scripts. Second, it supports custom trigger commands (“enter debugger mode”, “use thinking mode”) that allow users to launch workflows from natural language inputs. Third, you can define execution strategies—sequential, parallel, or dynamic based on context—to control how tools are used within a workflow. Finally, the server integrates seamlessly with any MCP client: once registered, your workflows become first‑class actions that can be invoked just like built‑in tools.

Real‑world scenarios benefit from this orchestration. A product team can maintain a library of PRD and roadmap templates that automatically pull in stakeholder notes, generate user stories, and produce release plans. A development team can bundle debugging workflows that fetch logs, run linters, and suggest fixes—all triggered by a single command. Because workflows are stored in plain YAML, they can be version‑controlled with Git, ensuring reproducibility and auditability across releases.

Workflows MCP stands out by reducing token overhead. Instead of embedding large rule sets into every prompt, the server routes calls to specialized tools and prompts, keeping each request lean. This deterministic approach not only saves cost but also improves consistency across interactions. For teams building AI‑augmented IDEs or chatbots, Workflows MCP offers a clear, maintainable path to scale complex tool usage while keeping context windows manageable.