Specs Workflow▌
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.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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
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:
- Change
./specsto your preferred documentation directory path- 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:
- Open VS Code with Cline extension
- Open Cline settings (gear icon)
- Navigate to MCP Servers section
- Add new server with:
- Command:
npx - Arguments:
-y spec-workflow-mcp@latest
- Command:
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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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.
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Ratings
4.5★★★★★71 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.
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