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

$3

- Feature details, PRDs, and implementation plans
- Progress reports and status tracking
- Phase and task details

$3

- 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

$3

- 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

$3

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

$3

You can use the save_document tool to save documents to custom locations:

``json
{
"featureId": "feature-123",
"documentType": "prd",
"filePath": "/custom/path/feature-123-prd.md"
}
`

$3

To get the path of a document, use the get_document_path tool:

`json
{
"featureId": "feature-123",
"documentType": "prd"
}
`

This returns both the path and whether the document has been saved to disk.

Development

Install dependencies:
`bash
npm install
`

Build the server:
`bash
npm run build
`

For development with auto-rebuild:
`bash
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

`json
{
"mcpServers": {
"vibe-coder-mcp": {
"command": "/path/to/vibe-coder-mcp/build/mcp-server.js"
}
}
}
`

$3

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

`bash
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.

`typescript
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