RealWorker-Manager MCP Server
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., "@RealWorker-Manager MCP ServerShow me the status of all workers"
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.
MCP Admin Server Architecture
Overview
This is a Manager/Admin MCP (Model Context Protocol) Server that coordinates and monitors multiple worker MCP servers across a distributed network. It acts as a centralized control plane for managing worker nodes. This is a Manager/Admin MCP (Model Context Protocol) Server that coordinates and monitors multiple worker MCP servers across a distributed network. It acts as a centralized control plane for managing worker nodes.
Related MCP server: MCP Gateway (Parent MCP Server)
Architecture Diagram
┌─────────────────────────────────────────────────────────────────┐
│ MCP Client (Claude/AI) │
│ │
└───────────────────────────┬─────────────────────────────────────┘
│ STDIO
│ (Standard Input/Output)
│
┌───────────────────────────▼─────────────────────────────────────┐
│ ADMIN/MANAGER SERVER │
│ (admin_server/admin.py) │
│ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ FastMCP Server Core │ │
│ │ - Server Name: "Manager" │ │
│ │ - Transport: STDIO │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ Management Tools │ │
│ │ │ │
│ │ 1. get_all_workers_status() │ │
│ │ - Polls all workers simultaneously │ │
│ │ - Returns aggregated status │ │
│ │ │ │
│ │ 2. get_worker_status(worker_name) │ │
│ │ - Gets status from specific worker │ │
│ │ - Returns detailed worker info │ │
│ │ │ │
│ │ 3. list_workers() │ │
│ │ - Lists all configured workers │ │
│ │ - Returns worker URLs │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ Worker Registry (WORKERS dict) │ │
│ │ │ │
│ │ Worker-One: http://10.149.14.61:8000 │ │
│ │ [Additional workers can be added here] │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
└───────────┬─────────────────────────────────┬───────────────────┘
│ HTTP/HTTPX │ HTTP/HTTPX
│ (Async Client) │ (Async Client)
│ │
┌───────────▼─────────────┐ ┌──────────▼──────────────┐
│ WORKER-ONE SERVER │ │ WORKER-N SERVER │
│ (10.149.14.61:8000) │ │ (Additional Workers) │
│ │ │ │
│ ┌──────────────────┐ │ │ ┌──────────────────┐ │
│ │ MCP Worker Core │ │ │ │ MCP Worker Core │ │
│ │ - SSE Endpoints │ │ │ │ - SSE Endpoints │ │
│ │ - Tool Handler │ │ │ │ - Tool Handler │ │
│ └──────────────────┘ │ │ └──────────────────┘ │
│ │ │ │
│ ┌──────────────────┐ │ │ ┌──────────────────┐ │
│ │ Worker Tools │ │ │ │ Worker Tools │ │
│ │ - System Status │ │ │ │ - System Status │ │
│ │ - Battery Info │ │ │ │ - Battery Info │ │
│ │ - Custom Tasks │ │ │ │ - Custom Tasks │ │
│ └──────────────────┘ │ │ └──────────────────┘ │
│ │ │ │
└─────────────────────────┘ └─────────────────────────┘Component Details
1. Admin/Manager Server (admin.py)
Purpose: Central coordination server that manages multiple worker MCP servers
Key Components:
FastMCP Core: Lightweight MCP server framework
Worker Registry: Dictionary mapping worker names to URLs
HTTP Client: Async HTTPX client for worker communication
Management Tools: Three exposed tools for worker management
Communication:
Upstream (to AI Client): STDIO transport
Downstream (to Workers): HTTP POST requests to worker SSE endpoints
2. Worker Servers
Purpose: Distributed worker nodes that perform actual tasks and report status
Key Components:
MCP Server Core: Handles incoming requests via SSE
Tool Endpoints:
/sse/tools/callfor tool executionStatus Tools:
get_worker_status()and other worker-specific tools
Communication:
Upstream (to Admin): HTTP responses to manager requests
Local Resources: Access to system information (CPU, memory, battery, etc.)
Data Flow
Scenario 1: Get All Workers Status
1. AI Client → Admin: Call get_all_workers_status()
2. Admin → Worker-One: POST /sse/tools/call (get_worker_status)
3. Admin → Worker-N: POST /sse/tools/call (get_worker_status)
[Parallel async requests]
4. Worker-One → Admin: Return status data
5. Worker-N → Admin: Return status data
6. Admin → AI Client: Aggregated results from all workersScenario 2: Get Specific Worker Status
1. AI Client → Admin: Call get_worker_status("Worker-One")
2. Admin: Lookup worker URL from WORKERS registry
3. Admin → Worker-One: POST /sse/tools/call (get_worker_status)
4. Worker-One → Admin: Return status data
5. Admin → AI Client: Worker statusScenario 3: List Workers
1. AI Client → Admin: Call list_workers()
2. Admin: Return WORKERS dictionary
3. Admin → AI Client: List of workers with URLsTechnical Stack
Core Technologies
Python 3.11+: Runtime environment
FastMCP: MCP server framework
HTTPX: Async HTTP client for worker communication
STDIO: Transport protocol for AI client communication
Dependencies
httpx>=0.28.1 # Async HTTP client
mcp[cli]>=1.26.0 # MCP framework
psutil>=7.2.2 # System monitoring (likely used by workers)
uvicorn>=0.40.0 # ASGI server (for workers)Deployment Architecture
Network Layer:
┌─────────────────────────────────────────────────────────┐
│ Local Network / VPN │
│ │
│ Admin Server Worker-One Worker-N │
│ (localhost) (10.149.14.61) (10.x.x.x) │
│ │
└─────────────────────────────────────────────────────────┘Deployment Characteristics:
Admin runs locally and communicates via STDIO with AI client
Workers are distributed across network (LAN/VPN)
HTTP-based communication between admin and workers
10-second timeout for worker requests
Async/parallel communication for efficiency
Security Considerations
Network Security:
Workers expose HTTP endpoints (currently unencrypted)
Should be deployed on trusted network or use VPN
Consider adding HTTPS/TLS for production
Authentication:
Currently no authentication between admin and workers
Consider adding API keys or mutual TLS
Error Handling:
Graceful degradation when workers are unavailable
Timeout protection (10s) prevents hanging
Scalability
Current Design:
Synchronous registry (WORKERS dict)
Hardcoded worker URLs
Manual configuration
Future Improvements:
Service discovery mechanism
Dynamic worker registration
Health check automation
Load balancing across workers
Worker heartbeat monitoring
Extension Points
Add New Worker: Update WORKERS dictionary with new worker URL
Add New Tool: Define new
@mcp.tool()function in admin.pyCustom Worker Communication: Extend HTTP client logic
Monitoring: Add logging, metrics collection, alerting
Usage Example
# From AI Client (Claude)
# The admin server exposes these tools:
# 1. List all configured workers
list_workers()
# Returns: {"workers": {"Worker-One": "http://10.149.14.61:8000"}}
# 2. Get status from all workers
get_all_workers_status()
# Returns: {"Worker-One": {...status data...}}
# 3. Get status from specific worker
get_worker_status("Worker-One")
# Returns: {...status data from Worker-One...}Running the Server
# Development mode
uv run admin.py
# Production mode (via MCP configuration)
# Add to Claude Desktop config:
{
"mcpServers": {
"admin-server": {
"command": "uv",
"args": ["run", "admin.py"],
"cwd": "d:\\SLT\\AI\\MCP_Servers\\admin_server"
}
}
}Project Structure
admin_server/
├── admin.py # Main admin/manager server
├── main.py # Alternative entry point (unused)
├── pyproject.toml # Project dependencies
└── README.md # This architecture documentThis server cannot be installed
Maintenance
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