developer-toolsproductivity

Specs Workflow

kingkongshot

by kingkongshot

Streamline project docs with Specs Workflow: automate software project plan templates, tracking, and OpenAPI-driven prog

Guides users through structured software project documentation phases with automated document generation, progress tracking, and workflow state management using OpenAPI specifications as templates.

github stars

128

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Persistent progress across conversationsPrevents AI from jumping randomly between tasksComplete traceability from user stories to implementation

best for

  • / Software developers planning new projects
  • / Teams needing systematic development documentation
  • / AI-assisted coding projects requiring structure
  • / Projects requiring traceability from requirements to code

capabilities

  • / Initialize structured software project workflows
  • / Generate requirements, design, and task documents
  • / Track project progress across development phases
  • / Resume workflows from previous sessions
  • / Complete tasks individually or in batches
  • / Validate workflow state and phase transitions

what it does

Guides AI assistants through a structured software development workflow (Requirements → Design → Tasks) with progress tracking and document generation. Uses OpenAPI specifications as templates to ensure systematic project documentation.

about

Specs Workflow is a community-built MCP server published by kingkongshot that provides AI assistants with tools and capabilities via the Model Context Protocol. Streamline project docs with Specs Workflow: automate software project plan templates, tracking, and OpenAPI-driven prog It is categorized under developer tools, productivity. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.

how to install

You can install Specs Workflow in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Specs Workflow is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Spec Workflow MCP

npm version License: MIT MCP

English | 简体中文

Guide AI to systematically complete software development through a structured Requirements → Design → Tasks workflow, ensuring code implementation stays aligned with business needs.

Why Use It?

❌ Without Spec Workflow

  • AI jumps randomly between tasks, lacking systematic approach
  • Requirements disconnect from actual code implementation
  • Scattered documentation, difficult to track project progress
  • Missing design decision records

✅ With Spec Workflow

  • AI completes tasks sequentially, maintaining focus and context
  • Complete traceability from user stories to code implementation
  • Standardized document templates with automatic progress management
  • Each stage requires confirmation, ensuring correct direction
  • Persistent progress: Continue from where you left off with check, even in new conversations

Recent Updates

v1.0.7

  • 🎯 Improved reliability for most models to manage tasks with spec workflow

v1.0.6

  • ✨ Batch task completion: Complete multiple tasks at once for faster progress on large projects

v1.0.5

  • 🐛 Edge case fixes: Distinguish between "task not found" and "task already completed" to prevent workflow interruption

v1.0.4

  • ✅ Task management: Added task completion tracking for systematic project progression

v1.0.3

  • 🎉 Initial release: Core workflow framework for Requirements → Design → Tasks

Quick Start

1. Install (Claude Code Example)

claude mcp add spec-workflow-mcp -s user -- npx -y spec-workflow-mcp@latest

See full installation guide for other clients.

2. Start a New Project

"Help me use spec workflow to create a user authentication system"

3. Continue Existing Project

"Use spec workflow to check ./my-project"

The AI will automatically detect project status and continue from where it left off.

Workflow Example

1. You describe requirements

You: "I need to build a user authentication system"

2. AI creates structured documents

AI: "I'll help you create spec workflow for user authentication..."

📝 requirements.md - User stories and functional requirements
🎨 design.md - Technical architecture and design decisions
✅ tasks.md - Concrete implementation task list

3. Review and implement step by step

After each stage, the AI requests your confirmation before proceeding, ensuring the project stays on the right track.

Document Organization

Basic Structure

my-project/specs/
├── requirements.md              # Requirements: user stories, functional specs
├── design.md                    # Design: architecture, APIs, data models
├── tasks.md                     # Tasks: numbered implementation steps
└── .workflow-confirmations.json # Status: automatic progress tracking

Multi-module Projects

my-project/specs/
├── user-authentication/         # Auth module
├── payment-system/             # Payment module
└── notification-service/       # Notification module

You can specify any directory: "Use spec workflow to create auth docs in ./src/features/auth"

AI Usage Guide

🤖 Make AI Use This Tool Better

Strongly recommended to add the following prompt to your AI assistant configuration. Without it, AI may:

  • ❌ Not know when to invoke Spec Workflow
  • ❌ Forget to manage task progress, causing disorganized work
  • ❌ Not utilize Spec Workflow for systematic documentation
  • ❌ Unable to continuously track project status

With this configuration, AI will intelligently use Spec Workflow to manage the entire development process.

Configuration Note: Please modify the following based on your needs:

  1. Change ./specs to your preferred documentation directory path
  2. Change "English" to your preferred documentation language (e.g., "Chinese")
# Spec Workflow Usage Guidelines

## 1. Check Project Progress
When user mentions continuing previous project or is unsure about current progress, proactively use:
specs-workflow tool with action.type="check" and path="./specs"

## 2. Documentation Language
All spec workflow documents should be written in English consistently, including all content in requirements, design, and task documents.

## 3. Documentation Directory
All spec workflow documents should be placed in ./specs directory to maintain consistent project documentation organization.

## 4. Task Management
Always use the following to manage task progress:
specs-workflow tool with action.type="complete_task" and taskNumber="current task number"
Follow the workflow guidance to continue working until all tasks are completed.

## 5. Best Practices
- Proactive progress check: When user says "continue from last time", first use check to see current status
- Language consistency: Use the same language throughout all project documents
- Flexible structure: Choose single-module or multi-module organization based on project scale
- Task granularity: Each task should be completable within 1-2 hours

Installation

<details> <summary>📦 Installation Instructions</summary>

Requirements

  • Node.js ≥ v18.0.0
  • npm or yarn
  • Claude Desktop or any MCP-compatible client

Install in Different MCP Clients

Claude Code (Recommended)

Use the Claude CLI to add the MCP server:

claude mcp add spec-workflow-mcp -s user -- npx -y spec-workflow-mcp@latest

Claude Desktop

Add to your Claude Desktop configuration:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%/Claude/claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "spec-workflow": {
      "command": "npx",
      "args": ["-y", "spec-workflow-mcp@latest"]
    }
  }
}

Cursor

Add to your Cursor configuration (~/.cursor/config.json):

{
  "mcpServers": {
    "spec-workflow": {
      "command": "npx",
      "args": ["-y", "spec-workflow-mcp@latest"]
    }
  }
}

Cline

Use Cline's MCP server management UI to add the server:

  1. Open VS Code with Cline extension
  2. Open Cline settings (gear icon)
  3. Navigate to MCP Servers section
  4. Add new server with:
    • Command: npx
    • Arguments: -y spec-workflow-mcp@latest

Windsurf (Codeium)

Add to your Windsurf configuration (~/.codeium/windsurf/mcp_config.json):

{
  "mcpServers": {
    "spec-workflow": {
      "command": "npx",
      "args": ["-y", "spec-workflow-mcp@latest"],
      "env": {},
      "autoApprove": [],
      "disabled": false,
      "timeout": 60,
      "transportType": "stdio"
    }
  }
}

VS Code (with MCP extension)

Add to your VS Code settings (settings.json):

{
  "mcp.servers": {
    "spec-workflow": {
      "command": "npx",
      "args": ["-y", "spec-workflow-mcp@latest"]
    }
  }
}

Zed

Add to your Zed configuration (~/.config/zed/settings.json):

{
  "assistant": {
    "version": "2",
    "mcp": {
      "servers": {
        "spec-workflow": {
          "command": "npx",
          "args": ["-y", "spec-workflow-mcp@latest"]
        }
      }
    }
  }
}

Install from Source

git clone https://github.com/kingkongshot/specs-mcp.git
cd specs-mcp
npm install
npm run build

Then add to Claude Desktop configuration:

{
  "mcpServers": {
    "spec-workflow": {
      "command": "node",
      "args": ["/absolute/path/to/specs-mcp/dist/index.js"]
    }
  }
}
</details>

Links

License

MIT License


<a href="https://glama.ai/mcp/servers/@kingkongshot/specs-workflow-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@kingkongshot/specs-workflow-mcp/badge" alt="Spec Workflow MCP server" /> </a>

FAQ

What is the Specs Workflow MCP server?
Specs Workflow is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Specs Workflow?
This profile displays 71 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.571 reviews
  • Daniel Sethi· Dec 28, 2024

    According to our notes, Specs Workflow benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Daniel Reddy· Dec 24, 2024

    I recommend Specs Workflow for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Harper Rahman· Dec 20, 2024

    Specs Workflow is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Harper Okafor· Dec 20, 2024

    We wired Specs Workflow into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Pratham Ware· Dec 8, 2024

    I recommend Specs Workflow for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Tariq Rahman· Dec 8, 2024

    According to our notes, Specs Workflow benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Amelia Chawla· Dec 4, 2024

    We wired Specs Workflow into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Nov 27, 2024

    Strong directory entry: Specs Workflow surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Amina Smith· Nov 27, 2024

    Specs Workflow has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Nikhil Malhotra· Nov 23, 2024

    We evaluated Specs Workflow against two servers with overlapping tools; this profile had the clearer scope statement.

showing 1-10 of 71

1 / 8