Vibe-Coder
A structured development workflow for LLM-based coding, including feature clarification, planning, phased development, and progress tracking.
Vibe-Coder MCP Server
A Model Context Protocol server that implements a structured development workflow for LLM-based coding.
Overview
This MCP server helps LLMs build features in an organized, clean, and safe manner by providing:
- A structured feature clarification process with guided questions
- PRD and implementation plan generation
- Phased development with task tracking
- Progress tracking and status reporting
- Document storage and retrieval capabilities
Features
Resources
- Feature details, PRDs, and implementation plans
- Progress reports and status tracking
- Phase and task details
Tools
start_feature_clarification- Begin the feature clarification processprovide_clarification- Answer clarification questions about a featuregenerate_prd- Generate a Product Requirements Document and implementation plancreate_phase- Create a development phase for a featureadd_task- Add tasks to a development phaseupdate_phase_status- Update the status of a phaseupdate_task_status- Update the completion status of a taskget_next_phase_action- Get guidance on what to do nextget_document_path- Get the path of a generated documentsave_document- Save a document to a specific location
Prompts
feature-planning- A prompt template for planning feature development
Document Storage
The server includes a hybrid document storage system that:
- Automatically saves generated documents (PRDs, implementation plans) to files
- Maintains an in-memory copy for quick access
- Allows clients to retrieve document paths and save to custom locations
Default Storage Location
Documents are stored in the documents/{featureId}/ directory by default, with filenames based on document type:
documents/{featureId}/prd.md- Product Requirements Documentdocuments/{featureId}/implementation-plan.md- Implementation Plan
Custom Storage
You can use the save_document tool to save documents to custom locations:
{
"featureId": "feature-123",
"documentType": "prd",
"filePath": "/custom/path/feature-123-prd.md"
}
Path Retrieval
To get the path of a document, use the get_document_path tool:
{
"featureId": "feature-123",
"documentType": "prd"
}
This returns both the path and whether the document has been saved to disk.
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Installation
To use with compatible MCP clients:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"vibe-coder-mcp": {
"command": "/path/to/vibe-coder-mcp/build/mcp-server.js"
}
}
}
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
Implementation Notes
This server is implemented using the high-level McpServer class from the Model Context Protocol TypeScript SDK, which simplifies the process of creating MCP servers by providing a clean API for defining resources, tools, and prompts.
import { McpServer, ResourceTemplate } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
// Create an MCP server
const server = new McpServer({
name: "Vibe-Coder",
version: "0.3.0"
});
// Add a resource
server.resource(
"features-list",
"features://list",
async (uri) => ({ /* ... */ })
);
// Add a tool
server.tool(
"start_feature_clarification",
{ /* parameters schema */ },
async (params) => ({ /* ... */ })
);
// Add a prompt
server.prompt(
"feature-planning",
{ /* parameters schema */ },
(params) => ({ /* ... */ })
);
// Start the server
const transport = new StdioServerTransport();
await server.connect(transport);
Workflow
The Vibe-Coder MCP server is designed to guide the development process through the following steps:
- Feature Clarification: Start by gathering requirements and understanding the feature's purpose, target users, and constraints
- Documentation: Generate a PRD and implementation plan based on the clarified requirements
- Phased Development: Break down the implementation into logical phases with clear tasks
- Progress Tracking: Monitor the completion of tasks and phases to guide development
- Completion: Verify that all requirements have been implemented and the feature is ready for use
Serveurs connexes
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
SelfHeal MCP
Self-healing proxy for MCP servers — retry, circuit breaker, fallback chains, and observability.
WOOFi Pro
Provides over 40 comprehensive trading tools for WOOFi Pro and Orderly Network integration.
Mezmo MCP
Mezmo's remote MCP server connects AI assistants to Mezmo's Observability platform so you can run advanced root-cause analysis, discover pipelines, and export logs without hosting anything yourself.
Unity Code MCP Server
Powerful tool for the Unity Editor that gives AI Agents ability to perform any action using Unity Editor API, like modification of scripts, scenes, prefabs, assets, configuration and more.
Agent Skill Loader
MCP server to dynamically load Claude Code skills into AI agents
InstaDomain
Domain registration for AI agents. Check, suggest, and buy domains via Stripe or x402 crypto. Cloudflare DNS auto-configured.
ZeroPath MCP Server
Interact with your product security findings using natural language.
MCP-Mem0
Integrate long-term memory into AI agents using Mem0.
ENC Charts MCP Server
Programmatically access and parse NOAA Electronic Navigational Charts (ENC) in S-57 format.
Tempo MCP Server
An MCP server for querying distributed tracing data from Grafana Tempo.