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Vibe-Coder MCP Server

Vibe-Coder MCP Server

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github.com/crazyrabbitLTCDeveloper Tools17Updated 84w ago

About Vibe-Coder MCP Server

Vibe-Coder MCP Server provides a structured development workflow for LLM-based coding. It is for developers who want to organize feature clarification, planning, and progress tracking, with phased implementation and saved documents managed through MCP tools, resources, and prompts.

Key features

  1. 01Guided feature clarification
  2. 02Generate PRDs and implementation plans
  3. 03Break work into development phases
  4. 04Track phase and task status
  5. 05Development resources and planning prompt
  6. 06Save and retrieve generated documents

Use cases

  1. 01Turn an initial idea into clarified requirements
  2. 02Generate a PRD and implementation plan
  3. 03Organize and track phased development tasks
  4. 04Save or retrieve planning documents

MCP support

It exposes tools for requirement clarification, document generation, and phase and task management, along with feature, plan, and progress resources. It also provides the `feature-planning` prompt.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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

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