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

Streamlines development workflows through AI-assisted codebase analysis, comprehensive planning, task breakdown with dependencies, and automated implementation verification. Enables systematic approach to complex development tasks like framework migrations and feature implementation.

Enables multi-agent code review and iterative improvement loop using different LLM backends, with deterministic scoring and audit trail.

Automates GitHub workflows (branch creation, testing, commit/push, PR) through natural language instructions in Claude Code.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

Delegates autonomous coding tasks to Z.ai's GLM models with a genuine agent loop, file operations, and verification via git and real process results.

Provides a specification-driven workflow layer for AI-assisted coding, enabling agents to follow an explicit 11-phase feature workflow with checkpoints, artifacts, and quality gates.

Acts as a unified dispatch hub for local coding agent CLIs, supporting capability-based routing, schema validation, and retries via MCP tools.

Automatically generates compelling application specifications and code based on the four dimensions (existence, historicity, relationality, irrationality), simplicity, and Figma-like UI, enabling users to create great apps without detailed instructions.

An MCP server that implements a structured workflow for LLM-based coding, guiding development through feature clarification, documentation generation, phased implementation, and progress tracking.

An MCP bridge that enables AI coding agents to delegate implementation tasks to the OpenAI Codex CLI, allowing the orchestrator to plan and review while Codex executes.

An MCP server that splits coding work between ChatGPT web (planning, review) and Codex CLI (implementation), enabling agentic workflows over a local repo with risk-gated execution and safety rails.

Bridges Claude Code and OpenAI Codex CLI for an interactive plan-execute-review workflow, enabling Claude to interview, design, and review while Codex implements code changes.

A stdio MCP server that lets Codex Desktop/CLI delegate implementation tasks to Claude Code CLI with workspace validation, Git status checks, and session resume capabilities.

An MCP server that reverse-engineers a rebuild spec (CLAUDE.md, config, and mutation-tested tests) from an existing app, enabling coding agents to rebuild the app cleanly against that spec.

MCP server that lets Claude Code ask GPT Codex for adversarial planning, code review, debugging, research, and risk triage without leaving your project workflow.

Official implementation of Anthropic's 'think' tool that provides Claude with a dedicated space for structured reasoning, improving performance by up to 54% on complex tasks requiring multi-step problem solving.

Provides unified access to multiple CLI AI agents (Codex, Gemini, Claude, and OpenCode) through a single MCP interface with real-time task monitoring, enabling specialized code analysis, UI design, implementation, and prototyping workflows.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

MCP server that provides AI coding agents automatic access to AGENTS.md documentation from GitHub repositories, enabling understanding of codebase conventions and patterns.

Coordinates Codex and Antigravity CLI for a structured software development workflow with workspace authorization, Git-based verification, and acceptance criteria.