MAGG
MAGG functions as a meta-MCP server that aggregates and manages multiple MCP servers, enabling LLMs to dynamically extend their capabilities.
Dynamic Server Management: Add, remove, enable, and disable MCP servers.
Tool Aggregation & Proxying: Access tools, resources, and prompts from multiple MCP servers through a unified interface.
Intelligent Configuration: Configure and add servers from URLs using LLM sampling.
Health Monitoring: Check server health, handle unresponsive servers, and view statistics.
Discovery: Search for and discover new MCP servers online.
Customization: Assign prefixes to tools for organized access and reload configurations dynamically.
Authentication Support: Secure access with optional RSA-based JWT authentication.
Provides ability to discover and integrate MCP servers hosted on GitHub repositories, fetching setup instructions and configuration details directly from source.
Enables installation and management of Python-based MCP servers published on PyPI, with version tracking and dependency management.
Supports Python-based MCP servers with automatic configuration and tool proxying capabilities.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MAGGsearch for weather-related MCP servers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🧲 Magg - The MCP Aggregator
A Model Context Protocol server that manages, aggregates, and proxies other MCP servers, enabling LLMs to dynamically extend their own capabilities.
What is Magg?
Magg is a meta-MCP server that acts as a central hub for managing multiple MCP servers. It provides tools that allow LLMs to:
Search for new MCP servers and discover setup instructions
Add and configure MCP servers dynamically
Enable/disable servers on demand
Aggregate tools from multiple servers under unified prefixes
Persist configurations across sessions
Think of Magg as a "package manager for LLM tools" - it lets AI assistants install and manage their own capabilities at runtime.
Related MCP server: mcp-llm
Features
Self-Service Tool Management: LLMs can search for and add new MCP servers without human intervention.
Dynamic Configuration Reloading: Automatically detects and applies config changes without restarting.
Automatic Tool Proxying: Tools from added servers are automatically exposed with configurable prefixes.
ProxyMCP Tool: A built-in tool that proxies the MCP protocol to itself, for clients that don't support notifications or dynamic tool updates (which is most of them currently).
Smart Configuration: Uses MCP sampling to intelligently configure servers from just a URL.
Persistent Configuration: Maintains server configurations in
.magg/config.json.Multiple Transport Support: Works with stdio, HTTP, and in-memory transports.
Bearer Token Authentication: Optional RSA-based JWT authentication for secure HTTP access.
Docker Support: Pre-built images for production, staging, and development workflows.
Health Monitoring: Built-in
magg_statusandmagg_checktools for server health checks.Real-time Messaging: Full support for MCP notifications and messages - receive tool/resource updates and progress notifications from backend servers.
Python 3.12+ Support: Fully compatible with Python 3.12 and 3.13.
Kit Management: Bundle related MCP servers into kits for easy loading/unloading as a group.
MBro CLI: Included MCP Browser for interactive exploration and management of MCP servers, with script support for automation.
Installation
Prerequisites
Python 3.12 or higher (3.13+ recommended)
uv(recommended) - Install from astral.sh/uv
Quick Install (Recommended)
The easiest way to install Magg is as a tool using uv:
# Install Magg as a tool
uv tool install magg
# Run with stdio transport (for Claude Desktop, Cline, etc.)
magg serve
# Run with HTTP transport (for system-wide access)
magg serve --httpAlternative: Run Directly from GitHub
You can also run Magg directly from GitHub without installing:
# Run with stdio transport
uvx --from git+https://github.com/sitbon/magg.git magg
# Run with HTTP transport
uvx --from git+https://github.com/sitbon/magg.git magg serve --httpLocal Development
For development, clone the repository and install in editable mode:
# Clone the repository
git clone https://github.com/sitbon/magg.git
cd magg
# Install in development mode with dev dependencies
uv sync --dev
# Or with poetry
poetry install --with dev
# Run the CLI
magg --helpDocker
Magg is available as pre-built Docker images from GitHub Container Registry:
# Run production image (WARNING log level)
docker run -p 8000:8000 ghcr.io/sitbon/magg:latest
# Run with authentication (mount or set private key)
docker run -p 8000:8000 \
-v ~/.ssh/magg:/home/magg/.ssh/magg:ro \
ghcr.io/sitbon/magg:latest
# Or with environment variable
docker run -p 8000:8000 \
-e MAGG_PRIVATE_KEY="$(cat ~/.ssh/magg/magg.key)" \
ghcr.io/sitbon/magg:latest
# Run beta image (INFO log level)
docker run -p 8000:8000 ghcr.io/sitbon/magg:beta
# Run with custom config directory
docker run -p 8000:8000 \
-v /path/to/config:/home/magg/.magg \
ghcr.io/sitbon/magg:latestDocker Image Strategy
Magg uses a multi-stage Docker build with three target stages:
pro(Production): Minimal image with WARNING log level, suitable for production deploymentspre(Pre-production): Same as production but with INFO log level for staging/testing (available but not published)dev(Development): Includes development dependencies and DEBUG logging for troubleshooting
Images are automatically published to GitHub Container Registry with the following tags:
Version tags (from main branch):
1.2.3,1.2,dev,1.2-dev,1.2-dev-py3.12, etc.Branch tags (from beta branch):
beta,beta-devPython-specific dev tags:
beta-dev-py3.12,beta-dev-py3.13, etc.
Docker Compose
For easier management, use Docker Compose:
# Clone the repository
git clone https://github.com/sitbon/magg.git
cd magg
# Run production version
docker compose up magg
# Run staging version (on port 8001)
docker compose up magg-beta
# Run development version (on port 8008)
# This uses ./.magg/config.json for configuration
docker compose up magg-dev
# Build and run with custom registry
REGISTRY=my.registry.com docker compose build
REGISTRY=my.registry.com docker compose pushSee compose.yaml and .env.example for configuration options.
Usage
Running Magg
Magg can run in three modes:
Stdio Mode (default) - For integration with Claude Desktop, Cline, Cursor, etc.:
magg serveHTTP Mode - For system-wide access or web integrations:
magg serve --http --port 8000Hybrid Mode - Both stdio and HTTP simultaneously:
magg serve --hybrid magg serve --hybrid --port 8080 # Custom portThis is particularly useful when you want to use Magg through an MCP client while also allowing HTTP access. For example:
With Claude Code:
# Configure Claude Code to use Magg in hybrid mode claude mcp add magg -- magg serve --hybrid --port 42000With mbro:
# mbro hosts Magg and connects via stdio mbro connect magg "magg serve --hybrid --port 8080" # Other mbro instances can connect via HTTP mbro connect magg http://localhost:8080
Available Tools
Once Magg is running, it exposes the following tools to LLMs:
magg_list_servers- List all configured MCP serversmagg_add_server- Add a new MCP servermagg_remove_server- Remove a servermagg_enable_server/magg_disable_server- Toggle server availabilitymagg_search_servers- Search for MCP servers onlinemagg_list_tools- List all available tools from all serversmagg_smart_configure- Intelligently configure a server from a URLmagg_analyze_servers- Analyze configured servers and suggest improvementsmagg_status- Get server and tool statisticsmagg_check- Health check servers with repair actions (report/remount/unmount/disable)magg_reload_config- Reload configuration from disk and apply changesmagg_load_kit- Load a kit and its servers into the configurationmagg_unload_kit- Unload a kit and optionally its servers from the configurationmagg_list_kits- List all available kits with their statusmagg_kit_info- Get detailed information about a specific kit
Quick Inspection with MBro
Magg includes the mbro (MCP Browser) CLI tool for interactive exploration. A unique feature is the ability to connect to Magg in stdio mode for quick inspection:
# Connect mbro to a Magg instance via stdio (no HTTP server needed)
mbro connect local-magg magg serve
# Now inspect your Magg setup from the MCP client perspective
mbro:local-magg> call magg_status
mbro:local-magg> call magg_list_serversMBro also supports:
Scripts: Create
.mbrofiles with commands for automationShell-style arguments: Use
key=valuesyntax instead of JSONTab completion: Rich parameter hints after connecting
See the MBro Documentation for details.
Authentication
Magg supports optional bearer token authentication to secure access:
Quick Start
Initialize authentication (creates RSA keypair):
magg auth initGenerate a JWT token for clients:
# Generate token (displays on screen) magg auth token # Export as environment variable export MAGG_JWT=$(magg auth token -q)Connect with authentication:
Using
MaggClient(auto-loads from MAGG_JWT):from magg.client import MaggClient async def main(): async with MaggClient("http://localhost:8000/mcp") as client: tools = await client.list_tools()Using FastMCP with explicit token:
from fastmcp import Client from fastmcp.client import BearerAuth jwt_token = "your-jwt-token-here" async with Client("http://localhost:8000/mcp", auth=BearerAuth(jwt_token)) as client: tools = await client.list_tools()
Key Management
Keys are stored in
~/.ssh/magg/by defaultPrivate key can be set via
MAGG_PRIVATE_KEYenvironment variableTo disable auth, remove keys or set non-existent
key_pathin.magg/auth.json
Authentication Commands
magg auth init- Initialize authentication (generates RSA keypair)magg auth status- Check authentication configurationmagg auth token- Generate JWT tokenmagg auth public-key- Display public key (for verification)magg auth private-key- Display private key (for backup)
See examples/authentication.py for more usage patterns.
Configuration
Magg stores its configuration in .magg/config.json in your current working directory. This allows for project-specific tool configurations.
Dynamic Configuration Reloading
Magg supports automatic configuration reloading without requiring a restart:
Automatic file watching: Detects changes to
config.jsonand reloads automatically (uses watchdog when available)SIGHUP signal: Send
kill -HUP <pid>to trigger immediate reload (Unix-like systems)MCP tool: Use
magg_reload_configtool from any MCP clientSmart transitions: Only affected servers are restarted during reload
Configuration reload is enabled by default. You can control it with:
MAGG_AUTO_RELOAD=false- Disable automatic reloadingMAGG_RELOAD_POLL_INTERVAL=5.0- Set polling interval in seconds (when watchdog unavailable)
See Configuration Reload Documentation for detailed information.
Environment Variables
Magg supports several environment variables for configuration:
MAGG_CONFIG_PATH- Path to config file (default:.magg/config.json)MAGG_LOG_LEVEL- Logging level: DEBUG, INFO, WARNING, ERROR, CRITICAL (default: INFO)MAGG_STDERR_SHOW=1- Show stderr output from subprocess MCP servers (default: suppressed)MAGG_AUTO_RELOAD- Enable/disable config auto-reload (default: true)MAGG_RELOAD_POLL_INTERVAL- Config polling interval in seconds (default: 1.0)MAGG_READ_ONLY=true- Run in read-only modeMAGG_SELF_PREFIX- Prefix for Magg tools (default: "magg"). Tools will be named as{prefix}{sep}{tool}(e.g.,magg_list_servers)MAGG_PREFIX_SEP- Separator between prefix and tool name (default: "_")
Example configuration:
{
"servers": {
"calculator": {
"name": "calculator",
"source": "https://github.com/executeautomation/calculator-mcp",
"command": "npx @executeautomation/calculator-mcp",
"prefix": "calc",
"enabled": true
}
}
}Adding Servers
Servers can be added in several ways:
Using the LLM (recommended):
"Add the Playwright MCP server" "Search for and add a calculator tool"Manual configuration via
magg_add_server:name: playwright url: https://github.com/microsoft/playwright-mcp command: npx @playwright/mcp@latest prefix: pwDirect config editing: Edit
.magg/config.jsondirectly
Real-time Notifications with MaggClient
The MaggClient now supports real-time notifications from backend MCP servers:
from magg import MaggClient, MaggMessageHandler
# Using callbacks
handler = MaggMessageHandler(
on_tool_list_changed=lambda n: print("Tools changed!"),
on_progress=lambda n: print(f"Progress: {n.params.progress}")
)
async with MaggClient("http://localhost:8000/mcp", message_handler=handler) as client:
# Client will receive notifications while connected
tools = await client.list_tools()See Messaging Documentation for advanced usage including custom message handlers.
Kit Management
Magg supports organizing related MCP servers into "kits" - bundles that can be loaded and unloaded as a group:
# List available kits
magg kit list
# Load a kit (adds all its servers)
magg kit load web-tools
# Unload a kit (removes servers only in that kit)
magg kit unload web-tools
# Get information about a kit
magg kit info web-toolsYou can also manage kits programmatically through Magg's tools when connected via an MCP client:
magg_list_kits- List all available kitsmagg_load_kit- Load a kit and its serversmagg_unload_kit- Unload a kitmagg_kit_info- Get detailed kit information
Kits are JSON files stored in ~/.magg/kit.d/ or .magg/kit.d/ that define a collection of related servers. See Kit Documentation for details on creating and managing kits.
MBro Scripts
Automate common workflows with MBro scripts:
# Create a setup script
cat > setup.mbro <<EOF
# Connect to Magg and check status
connect magg magg serve
call magg_status
call magg_list_servers
# Add a new server if needed
call magg_add_server name=calculator source="npx -y @modelcontextprotocol/server-calculator"
EOF
# Run the script
mbro -x setup.mbroDocumentation
For more documentation, see docs/.
Appearances
Magg appears in multiple locations. Please feel free to submit a PR to add more appearances below in alphabetical order.
Listing, Index, and other MCP Sites
Awesome GitHub MCP Lists
Latest Blog Posts
MCP directory API
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