"Spec-WorkFlow documentation or implementation" matching MCP servers:

Provides structured spec-driven development workflow tools for AI-assisted software development, enabling spec creation, task tracking, approvals, and real-time monitoring via a web dashboard or VSCode extension.

Provides structured spec-driven development workflow tools for AI-assisted software development with sequential spec creation (Requirements → Design → Tasks). Features a real-time web dashboard for monitoring project progress and managing development workflows.

An intelligent MCP server that helps development teams maintain high-quality project documentation by providing an AI-powered workflow for creating comprehensive specifications through requirements, design, and implementation documents.

A comment-based spec-driven development MCP server that facilitates workflows from requirements creation to implementation via AI, using @spec-impl markers.

Enables AI coding tools to follow a structured spec-driven development workflow with three phases: requirements, design, and tasks, ensuring approval before advancing.

Provides MCP tools to score request sufficiency against a profile, block underspecified work, and write committed decision records with evidence and overrides.

A deterministic MCP server that checks project code alignment with SPEC documents through static analysis without AI involvement.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

A standalone runtime and MCP server that executes Claude Code dynamic workflow files through interchangeable agent providers, ensuring compatibility with Claude Code's workflow format.

Enables AI coding agents to collaboratively create and manage a specification roadmap persisted in PostgreSQL, progressing from constitution through specification, clarification, planning, task generation, and analysis, while exposing a get_next_task tool for implementation sessions.

Centralized MCP server for spec-driven AI agent workflows, enabling isolated feature management, task tracking, and implementation with handoff and archiving capabilities across multiple projects and developers.

A methodology and MCP server for agent-driven software development where humans write specs and agents implement code, enforced by six mechanical gates to ensure spec validity, contracts, tests, and review.

Enables AI agents to lint and format n8n workflow JSON over MCP, reporting issues with line-level detail and applying safe fixes.

Manages software project specifications with AI-powered guided creation, querying, validation, and dependency analysis through the Model Context Protocol.

Enables AI coding agents to verify code against YAML specifications, detecting missing fields, extra fields, and type mismatches to prevent silent drift before commits.

A NestJS MCP server that extracts tables from documents (PDF, etc.) into a single JSON file using OpenRouter's Claude Haiku model.

An MCP server that provides AI assistants with searchable access to the full s&box game engine documentation and API reference.

Bridge Figma designs to any platform with structured specs for Unity, React, Flutter, SwiftUI, and more, including layout audit, design tokens, and accessibility checks.

Generates professional documentation for multi-language projects with deep code analysis, supporting frameworks like Docusaurus, MkDocs, and Sphinx, including API docs, PDF export, and OpenAPI specifications.

Prevents premature AI coding by transforming vague product ideas into structured specifications, architecture decisions, and acceptance criteria through a series of interrogation and compilation tools.