Spec MCP Server
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.
README
Spec MCP Server
A Model Context Protocol server designed to streamline development workflows through AI-assisted analysis, planning, and verification.
Features
- Tech Steering: Automated codebase analysis and documentation
- Plan Generation: Comprehensive requirement and design documentation
- Task Breakdown: Detailed task generation with dependencies
- Implementation Verification: Automated code review and compliance checking
Installation
- Configure your AI client (Claude Desktop, Cursor, etc.)
- Add the server to your MCP configuration
- Start using the tools through your AI interface
Configuration Examples
Visual Studio Code
Add to your VS Code MCP configuration file:
- Regular VS Code:
~/Library/Application Support/Code/User/mcp.json - VS Code Insiders:
~/Library/Application Support/Code - Insiders/User/mcp.json
{
"servers": {
"spec": {
"command": "npx",
"args": [
"-y",
"spec-mcp@latest"
]
}
}
}
Zed
- Open Zed > Settings > Open Settings (it will open
~/. config/zed/settings.json) - Add a context_servers section to your configuration:
{
"context_servers": {
"spec": {
"source": "custom",
"command": "npx",
"args": ["-y", "spec-mcp@latest"],
"env": {}
}
}
}
Claude Code (CLI)
For Claude Code CLI, use the following command:
claude mcp add spec-mcp --scope user -- npx -y spec-mcp@latest
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"spec": {
"command": "npx",
"args": [
"-y",
"spec-mcp@latest"
]
}
}
}
Workflow
The Spec MCP workflow guides you through complex development tasks like framework migrations, feature implementation, or refactoring. Follow these steps:
1. Analyze Codebase (One-time Setup)
Analyze the existing codebase to create steering documents that guide all future operations.
Prompt: Use Spec MCP to analyze the codebase
This creates three steering documents in .spec/steering/:
product.md- Product overview and business contexttech.md- Technology stack and development guidelinesstructure.md- Project organization and patterns
Note: You can recreate these documents anytime with force_regenerate=true
2. Search Documentation
Search documentation for relevant information about frameworks, APIs, or migration guides using e.g. Context7 MCP.
Prompt: Search docs with Context7 MCP for [topic/framework/library]
3. Generate Plan
Create a comprehensive plan based on your requirements and the current codebase context.
Prompt: Create a plan with Spec MCP to [describe your objective]
This generates .spec/specs/plan.md with requirements, design, and traceability.
4. Generate Tasks
Break down the plan into actionable, testable tasks with dependencies.
Prompt: Generate tasks from the plan using Spec MCP
This creates .spec/specs/tasks.md with detailed implementation tasks.
5. Implement Tasks
Execute tasks systematically using the task orchestrator, which handles dependencies and parallelization.
Prompt: Implement tasks from tasks.md using Spec MCP task orchestrator
The orchestrator will:
- Identify ready tasks based on dependencies
- Execute tasks through task-executor
- Verify completion with task-checker
- Report progress and next available tasks
Available Tools
generate-codebase-analysis
Analyzes codebase and generates three foundational analysis documents: product.md, tech.md, and structure.md in .spec/steering/ directory. These documents provide comprehensive analysis of the product features, technology stack, and project structure.
generate-plan
Creates comprehensive plans from user requirements, combining requirements analysis with technical design.
generate-tasks
Breaks down plan.md into discrete, implementable tasks with requirement traceability, dependencies, and comprehensive acceptance criteria following task structure. Each task links back to specific requirements and includes detailed implementation guidance. Uses current directory if project_path not specified.
task-orchestrator
Analyzes tasks.md to identify dependencies, parallelization opportunities, and coordinate task execution. Returns a structured execution plan for deploying task executors efficiently.
task-executor
Executes a specific task from tasks.md by providing detailed implementation guidance, requirements, acceptance criteria, and code patterns. This tool focuses on implementing one task thoroughly.
verify-implementation
READ-ONLY verification tool that checks completed task implementation against acceptance criteria, runs EXISTING project tests, and reports quality status. This tool ONLY verifies and reports - it does NOT create or modify any files, tests, or code.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.