@merabylabs/meraby-daemon-mcp
v1.0.1
Published
MCP server for Meraby Daemon - AI-powered autonomous coding agent with workspace-aware tools.
Readme
@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
🔗 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 |
✨ Why Meraby Daemon MCP?
🎯 Workspace-Aware Intelligence
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.
🚀 Key Benefits
- 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
🛠️ Tools
| 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 |
📦 Resources
- Template Library: Reference templates for coding, writing, research, and analysis tasks
- Category Collections: Browse templates by category for inspiration
Installation
npm install @merabylabs/meraby-daemon-mcpOr install globally:
npm install -g @merabylabs/meraby-daemon-mcpUsage
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.
Claude Desktop
Add to your Claude Desktop configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}VS Code (GitHub Copilot)
Add to your VS Code settings.json (Cmd/Ctrl+Shift+P → "Preferences: Open Settings (JSON)"):
{
"github.copilot.chat.mcp.servers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}Cursor
Add to your Cursor MCP settings:
- macOS/Linux:
~/.cursor/mcp.json - Windows:
%USERPROFILE%\.cursor\mcp.json - Or via: Settings → MCP
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}Windsurf (Codeium)
Add to your Windsurf MCP configuration:
- macOS/Linux:
~/.codeium/windsurf/mcp_config.json - Windows:
%USERPROFILE%\.codeium\windsurf\mcp_config.json
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}Zed
Add to your Zed settings:
- macOS:
~/.config/zed/settings.json - Linux:
~/.config/zed/settings.json
{
"context_servers": {
"meraby-daemon": {
"command": {
"path": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
},
"settings": {}
}
}
}JetBrains IDEs
Works with IntelliJ IDEA, PyCharm, WebStorm, PhpStorm, GoLand, RubyMine, CLion, DataGrip, Rider, Android Studio.
- Install the MCP Client plugin from JetBrains Marketplace
- Go to Settings → Tools → MCP Servers
- Add a new server with this configuration:
{
"mcpServers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}Or add to .idea/mcp.json in your project.
Continue.dev
Add to your Continue configuration:
- Global:
~/.continue/config.json - Project:
.continue/config.json
{
"experimental": {
"modelContextProtocolServers": [
{
"transport": {
"type": "stdio",
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
]
}
}Cline
Add to your Cline MCP settings in VS Code:
{
"cline.mcp.servers": {
"meraby-daemon": {
"command": "npx",
"args": ["@merabylabs/meraby-daemon-mcp"]
}
}
}🔧 Configuration
Environment Variables
# 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.jsonProgrammatic Usage
import { createServer } from '@merabylabs/meraby-daemon-mcp';
const server = createServer();
// ... connect to your transport📊 How It Works
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Your IDE │────▶│ MCP Protocol │────▶│ Meraby Daemon │
│ (Claude, etc) │◀────│ (stdio/SSE) │◀────│ MCP Server │
└─────────────────┘ └─────────────────┘ └────────┬────────┘
│
▼
┌─────────────────┐
│ Vertex AI │
│ Gemini 3 Pro │
└─────────────────┘The MCP server:
- Receives tool calls from your IDE
- Executes workspace operations (read/write/search)
- Calls Vertex AI for intelligent processing
- Returns results via MCP protocol
🔒 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
📝 License
MIT License - see LICENSE for details.
🔗 Links
Built with 🔮 by Meraby Labs
