MCP Connector

Orchestrate MCP Servers for LLM Autonomy

Magg is a meta-MCP server that aggregates and proxies other MCP servers, letting LLMs dynamically add and manage them at runtime.

Works with github

90
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out of 100
Updated last month
Source checked Sep 15, 2026
Version 1.2.1
Models
universal

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Why it matters

Empower AI assistants to autonomously discover, install, and manage multiple MCP servers, expanding their capabilities on demand. This provides a universal hub for LLM-driven operational expansion.

Outcomes

What it gets done

01

Discover and install various MCP servers.

02

Orchestrate the deployment and management of MCP servers.

03

Enable LLMs to self-expand their functional scope.

04

Browse and script MCP server interactions via CLI.

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-magg-the-mcp-aggregator | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

Reports

Agent outcome reports

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Capabilities

Tools your agent gets

discover_mcp_servers

Discover available MCP servers that can be installed and used.

install_mcp_server

Install a specified MCP server to expand LLM capabilities.

orchestrate_mcp_servers

Orchestrate and manage multiple MCP servers working together.

browse_mcp_servers

Browse available MCP servers using the mbro CLI tool.

Overview

Magg: The MCP Aggregator MCP Server

Magg is a meta-MCP server that aggregates, proxies, and lets an LLM dynamically add, configure, enable, and disable other MCP servers at runtime, all behind one endpoint. It persists server configuration to a local file, reloads changes automatically, and groups related servers into loadable kits. A companion mbro CLI and MaggClient Python client let you inspect and script the aggregated setup. Use it when an LLM or MCP client needs to discover and manage its own MCP tool servers at runtime rather than a fixed, manually configured list. Skip it for a setup that only ever talks to one static MCP server.

What it does

Magg is a meta-MCP server that manages, aggregates, and proxies other MCP servers, giving LLMs a "package manager for LLM tools" they can use to search for, add, configure, and enable or disable MCP servers at runtime. It aggregates tools from every configured backend server under unified prefixes, persists that configuration in .magg/config.json across sessions, and automatically detects and applies config changes without a restart (via file watching, a SIGHUP signal, or the magg_reload_config tool). A built-in ProxyMCP tool re-exposes the aggregated protocol to clients that don't support notifications or dynamic tool updates, and a Smart Configuration feature uses MCP sampling to configure a new server from just a URL. Magg also bridges the MCP 2026-07-28 stateless spec: it keeps owning the long-lived stdio subprocesses, backend connections, and tool-list caching that a stateless request/response core doesn't provide on its own, connecting pre-2026 stateful backends to stateless-era clients, including in hierarchical Magg deployments.

When to use - and when NOT to

Use Magg when you want a single MCP endpoint that lets an LLM discover, install, and manage its own MCP tool servers at runtime instead of hand-editing a static client config for every server - for example, an assistant that searches for a Playwright or calculator MCP server and adds it on the fly, or a setup that groups related servers into "kits" that load and unload together. Magg runs in stdio mode (for Claude Desktop, Cline, Cursor, or Claude Code), HTTP mode for shared or system-wide access, or hybrid mode for both at once, and its transports include stdio, HTTP, and in-memory.

Skip Magg if you only ever connect to one fixed MCP server: aggregation, dynamic add/remove, and kit management add operational surface (a config file, optional bearer-token auth, health checks) that a single static server connection doesn't need.

Capabilities

Magg exposes tools to list, add, remove, enable, and disable backend MCP servers; search for new MCP servers online and smart-configure them from a URL; list all aggregated tools and analyze configured servers for improvements; check server and tool stats with magg_status and run health checks with repair actions via magg_check; and load, unload, list, and inspect "kits" - bundles of related servers - via magg_load_kit, magg_unload_kit, magg_list_kits, and magg_kit_info. Servers and kits can also be managed entirely from the command line with magg server and magg kit subcommands, without a running Magg instance or MCP client. Optional bearer-token authentication uses an RSA-based JWT (magg auth init / token / status), and the MaggClient Python client supports real-time notifications - tool-list-changed and progress events - via message handler callbacks. The included mbro (MCP Browser) CLI connects to a running Magg instance over stdio or HTTP for interactive inspection and scripted automation via .mbro files.

How to install

# 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 --http

Magg requires Python 3.12 or higher (3.13+ recommended) and is also available as a pre-built Docker image from GitHub Container Registry, or runnable directly from GitHub via uvx --from git+https://github.com/sitbon/magg.git magg.

Who it's for

Teams and individuals running MCP clients (Claude Desktop, Claude Code, Cline, Cursor, or custom MCP clients) who want their LLM to discover and manage its own MCP tool servers at runtime, rather than maintaining a fixed, manually configured list of servers per client.

Source README

🧲 Magg - The MCP Aggregator

Python Version
PyPI Version
GitHub Release
DeepWiki
Downloads

Tests
Docker

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.

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_status and magg_check tools 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 --http

Alternative: 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 --http

Local 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 --help

Docker

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:latest
Docker Image Strategy

Magg uses a multi-stage Docker build with three target stages:

  • pro (Production): Minimal image with WARNING log level, suitable for production deployments
  • pre (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-dev
  • Python-specific dev tags: beta-dev-py3.12, beta-dev-py3.13, etc.

Pull requests build and test images but do not publish them unless a maintainer adds the
push-image label, which publishes ephemeral pr-NN / pr-NN-dev tags (same-repo PRs
only). Ephemeral pr-* tags and untagged manifests are cleaned up weekly; version tags
are kept forever, so pinned deployments are never affected.

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 push

See compose.yaml and .env.example for configuration options.

Usage

Running Magg

Magg can run in three modes:

  1. Stdio Mode (default) - For integration with Claude Desktop, Cline, Cursor, etc.:

    magg serve
    
  2. HTTP Mode - For system-wide access or web integrations:

    magg serve --http --port 8000
    
  3. Hybrid Mode - Both stdio and HTTP simultaneously:

    magg serve --hybrid
    magg serve --hybrid --port 8080  # Custom port
    

    This 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 42000
    

    With 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 servers
  • magg_add_server - Add a new MCP server
  • magg_remove_server - Remove a server
  • magg_enable_server / magg_disable_server - Toggle server availability
  • magg_search_servers - Search for MCP servers online
  • magg_list_tools - List all available tools from all servers
  • magg_smart_configure - Intelligently configure a server from a URL
  • magg_analyze_servers - Analyze configured servers and suggest improvements
  • magg_status - Get server and tool statistics
  • magg_check - Health check servers with repair actions (report/remount/unmount/disable)
  • magg_reload_config - Reload configuration from disk and apply changes
  • magg_load_kit - Load a kit and its servers into the configuration
  • magg_unload_kit - Unload a kit and optionally its servers from the configuration
  • magg_list_kits - List all available kits with their status
  • magg_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_servers

MBro also supports:

  • Scripts: Create .mbro files with commands for automation
  • Shell-style arguments: Use key=value syntax instead of JSON
  • Tab completion: Rich parameter hints after connecting

See the MBro Documentation for details.

Authentication

Magg supports optional bearer token authentication to secure access:

Quick Start
  1. Initialize authentication (creates RSA keypair):

    magg auth init
    
  2. Generate a JWT token for clients:

    # Generate token (displays on screen)
    magg auth token
    
    # Export as environment variable
    export MAGG_JWT=$(magg auth token -q)
    
  3. 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 default
  • Private key can be set via MAGG_PRIVATE_KEY environment variable
  • To disable auth, remove keys or set non-existent key_path in .magg/auth.json
Authentication Commands
  • magg auth init - Initialize authentication (generates RSA keypair)
  • magg auth status - Check authentication configuration
  • magg auth token - Generate JWT token
  • magg 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.json and reloads automatically (uses watchdog when available)
  • SIGHUP signal: Send kill -HUP <pid> to trigger immediate reload (Unix-like systems)
  • MCP tool: Use magg_reload_config tool from any MCP client
  • Smart 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 reloading
  • MAGG_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 mode
  • MAGG_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:

  1. Using the LLM (recommended):

    "Add the Playwright MCP server"
    "Search for and add a calculator tool"
    
  2. Manual configuration via magg_add_server:

    name: playwright
    url: https://github.com/microsoft/playwright-mcp
    command: npx @playwright/mcp@latest
    prefix: pw
    
  3. The magg server CLI (see below)

  4. Direct config editing: Edit .magg/config.json directly

Managing Servers from the CLI

Server and kit configuration can be managed entirely from the command line - no MCP client
or running server required. The CLI edits .magg/config.json directly, and a running Magg
instance picks up the changes automatically via config reload.
(Tools that require a live server, like magg_search_servers, magg_check, and
magg_smart_configure, remain available through any MCP client such as mbro.)

# List servers (human-readable, or JSON on stdout for scripting)
magg server list
magg server list --json

# Add a server
magg server add playwright https://github.com/microsoft/playwright-mcp \
    --command "npx @playwright/mcp@latest" --prefix pw

# Add a server without enabling it, with transport options
magg server add web https://example.com/web --uri http://localhost:9000/mcp \
    --transport '{"keep_alive": false}' --disable

# Update an existing server (pass '' to clear an optional field)
magg server update playwright --prefix play --notes "Browser automation"
magg server update playwright --command "npx @playwright/mcp@next"
magg server update playwright --notes ""

# Enable / disable / inspect / remove
magg server enable playwright
magg server disable playwright
magg server info playwright --json
magg server remove playwright

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-tools

# Export the current configuration (or a loaded kit) as a kit file
magg kit export --name my-kit --output my-kit.json

When unloading a kit, servers that belong only to that kit are removed, while servers
shared with other kits are kept.

You can also manage kits programmatically through Magg's tools when connected via an MCP client:

  • magg_list_kits - List all available kits
  • magg_load_kit - Load a kit and its servers
  • magg_unload_kit - Unload a kit
  • magg_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.mbro

MCP 2026-07-28 (Stateless Spec)

The MCP 2026-07-28 spec moves the protocol to a stateless request/response core. Magg's take:
something still has to own long-lived stdio subprocesses, backend connections, and tool-list
caching - and that's exactly the layer an aggregator provides. See
Magg and the Stateless MCP Spec for the impact analysis and migration
plan, including how Magg bridges pre-2026 (stateful) backends to stateless-era clients and how
hierarchical Magg deployments fit in.

Documentation

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

  • DeepWiki - AI-generated documentation
  • Glama.ai - MCP server listing and hosting

Magg ships a server.json manifest for the
official MCP Registry (as io.github.sitbon/magg),
and magg_search_servers queries the registry as a first-class discovery source alongside
Glama, GitHub, and npm. See MCP Registry Documentation for publishing
instructions.

mcp-name: io.github.sitbon/magg

Awesome GitHub MCP Lists

FAQ

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