@merabylabs/meraby-daemon-mcp


> Meraby Daemon MCP Server — Your tireless background guardian for AI-powered development

A Model Context Protocol (MCP) server that provides autonomous coding capabilities powered by Vertex AI with Gemini 3 Pro. Part of the Meraby Daemon ecosystem — Watch, Plan, Execute.

Works with: Claude Desktop • VS Code (Copilot) • Cursor • Windsurf • Zed • JetBrains IDEs • Continue.dev • Cline

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🔗 Part of the Meraby Daemon Ecosystem

| Product | Description |
|---------|-------------|
| Meraby Daemon MCP | This package — MCP server for IDE integration |
| VS Code Extension | Full Daemon panel with autonomous agent capabilities |
| Web App | Full-featured web application |

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✨ Why Meraby Daemon MCP?

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Unlike generic AI tools, Meraby Daemon understands your project context. When executing tasks, it considers:

- Your tech stack — React, Node, Python, or whatever you're building with
- Project structure — File organization, naming conventions, architecture patterns
- Dependencies — Libraries and frameworks from your package.json/requirements.txt
- Your original request — Ensures actions stay aligned with your actual goal

This means AI assistance tailored to your specific codebase, not generic boilerplate.

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- No API key required — Powered by Vertex AI with Gemini 3 Pro
- Works in your IDE — Integrates with your existing workflow via MCP
- Context-aware — Actions that understand your project conventions
- Autonomous execution — Plan and execute multi-step tasks

Features

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| Tool | Description |
|------|-------------|
| generate_prompt | Transform ideas into well-structured prompts |
| refine_prompt | Improve prompts based on feedback and workspace context |
| analyze_prompt | Evaluate prompt quality with scores and suggestions |
| read_file | Read file contents from the workspace |
| write_file | Create or update files |
| list_files | List directory contents |
| search_files | Search for patterns across files |
| search_and_replace | Make targeted edits across files |
| get_workspace_context | Get project structure and tech stack |
| get_ast_context | Get code structure via AST analysis |
| index_workspace | Build semantic search index |
| semantic_search | Search code by meaning |
| execute_command | Run shell commands |
| run_npm_script | Execute npm scripts |
| git_command | Git operations |
| install_dependencies | Install packages |
| execute_prompt_workflow | Multi-step prompt refinement |
| execute_custom_workflow | Custom automation workflows |

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- Template Library: Reference templates for coding, writing, research, and analysis tasks
- Category Collections: Browse templates by category for inspiration

Installation

``bash
npm install @merabylabs/meraby-daemon-mcp
`

Or install globally:

`bash
npm install -g @merabylabs/meraby-daemon-mcp
`

Usage

Meraby Daemon MCP server works with any IDE or application that supports the Model Context Protocol. Below are configuration examples for popular editors.

> No API key required! The MCP server uses Vertex AI, so you don't need your own Gemini API key.

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Add to your Claude Desktop configuration file:
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json

`json
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}
`

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Add to your VS Code settings.json (Cmd/Ctrl+Shift+P → "Preferences: Open Settings (JSON)"):

`json
{
"github.copilot.chat.mcp.servers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}
`

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Add to your Cursor MCP settings:
- macOS/Linux: ~/.cursor/mcp.json
- Windows: %USERPROFILE%\.cursor\mcp.json
- Or via: Settings → MCP

`json
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}
`

📖 Cursor MCP Documentation

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Add to your Windsurf MCP configuration:
- macOS/Linux: ~/.codeium/windsurf/mcp_config.json
- Windows: %USERPROFILE%\.codeium\windsurf\mcp_config.json

`json
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}
`

📖 Windsurf MCP Documentation

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Add to your Zed settings:
- macOS: ~/.config/zed/settings.json
- Linux: ~/.config/zed/settings.json

`json
{
"context_servers": {
"meraby-daemon": {
"command": {
"path": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
},
"settings": {}
}
}
}
`

📖 Zed MCP Documentation

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Works with IntelliJ IDEA, PyCharm, WebStorm, PhpStorm, GoLand, RubyMine, CLion, DataGrip, Rider, Android Studio.

1. Install the MCP Client plugin from JetBrains Marketplace
2. Go to Settings → Tools → MCP Servers
3. Add a new server with this configuration:

`json
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}
`

Or add to .idea/mcp.json in your project.

📖 JetBrains MCP Plugin

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Add to your Continue configuration:
- Global: ~/.continue/config.json
- Project: .continue/config.json

`json
{
"experimental": {
"modelContextProtocolServers": [
{
"transport": {
"type": "stdio",
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
]
}
}
`

📖 Continue MCP Documentation

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Add to your Cline MCP settings in VS Code:

`json
{
"cline.mcp.servers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}
`

📖 Cline MCP Documentation

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🔧 Configuration

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`bash

For local development with API key fallback

GEMINI_API_KEY=your-key-here

For Vertex AI (production) - auto-detected in Google Cloud

GCLOUD_PROJECT=your-project-id
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json
`

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`typescript
import { createServer } from '@merabylabs/meraby-daemon-mcp';

const server = createServer();
// ... connect to your transport
`

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📊 How It Works

`
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Your IDE │────▶│ MCP Protocol │────▶│ Meraby Daemon │
│ (Claude, etc) │◀────│ (stdio/SSE) │◀────│ MCP Server │
└─────────────────┘ └─────────────────┘ └────────┬────────┘
│
▼
┌─────────────────┐
│ Vertex AI │
│ Gemini 3 Pro │
└─────────────────┘
``

The MCP server:
1. Receives tool calls from your IDE
2. Executes workspace operations (read/write/search)
3. Calls Vertex AI for intelligent processing
4. Returns results via MCP protocol

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🔒 Security

- No data storage: Your code never leaves your machine (except for AI processing)
- Vertex AI: Enterprise-grade security with IAM authentication
- Local execution: All file operations happen locally
- Audit logging: Full visibility in Google Cloud Console

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📝 License

MIT License - see LICENSE for details.

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🔗 Links

- Meraby Labs
- VS Code Extension
- GitHub
- Model Context Protocol

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Built with 🔮 by Meraby Labs