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mcp-vibecoder

MCP.Pizza Chef: crazyrabbitLTC

The mcp-vibecoder MCP server facilitates structured, phased development workflows for LLM-driven coding projects. It supports feature clarification, PRD and implementation plan generation, phased task management, progress tracking, and document storage. This server enables LLMs to build software features in an organized, clean, and safe manner by guiding through clarification questions, managing development phases and tasks, and reporting status updates, streamlining complex coding projects with real-time context and structured processes.

Use This MCP server To

Clarify software feature requirements with guided questions Generate detailed PRDs and implementation plans automatically Manage phased development with task creation and tracking Track progress and update status of development phases Store and retrieve project documents and reports Coordinate multi-step LLM-driven coding workflows Automate structured feature development processes

README

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 process
  • provide_clarification - Answer clarification questions about a feature
  • generate_prd - Generate a Product Requirements Document and implementation plan
  • create_phase - Create a development phase for a feature
  • add_task - Add tasks to a development phase
  • update_phase_status - Update the status of a phase
  • update_task_status - Update the completion status of a task
  • get_next_phase_action - Get guidance on what to do next
  • get_document_path - Get the path of a generated document
  • save_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:

  1. Automatically saves generated documents (PRDs, implementation plans) to files
  2. Maintains an in-memory copy for quick access
  3. 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 Document
  • documents/{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:

  1. Feature Clarification: Start by gathering requirements and understanding the feature's purpose, target users, and constraints
  2. Documentation: Generate a PRD and implementation plan based on the clarified requirements
  3. Phased Development: Break down the implementation into logical phases with clear tasks
  4. Progress Tracking: Monitor the completion of tasks and phases to guide development
  5. Completion: Verify that all requirements have been implemented and the feature is ready for use

mcp-vibecoder FAQ

How does mcp-vibecoder improve LLM-based coding workflows?
It structures feature development with guided clarifications, phased tasks, and progress tracking, enabling organized and safe coding processes.
Can mcp-vibecoder generate documentation?
Yes, it generates Product Requirements Documents (PRDs) and implementation plans to guide development.
How does mcp-vibecoder handle task management?
It allows creating development phases, adding tasks, and updating their status for detailed progress tracking.
Is document storage supported?
Yes, it supports storing and retrieving feature details, reports, and related documents.
What benefits does phased development provide?
Phased development breaks down features into manageable tasks, improving clarity and progress visibility.
Can mcp-vibecoder integrate with multiple LLM providers?
Yes, it is designed to work with various LLMs like OpenAI, Claude, and Gemini for flexible integration.
How does it ensure safe feature development?
By enforcing structured workflows and clear task definitions, it reduces errors and miscommunication.
What kind of projects is mcp-vibecoder best suited for?
It is ideal for complex software projects requiring organized, multi-step LLM-assisted development.