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

Related MCP server: DevFlow MCP Server

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