tunnel-manager — Concept Overview¶
Category: Infrastructure | Ecosystem Role: MCP Server + A2A Agent Built on
scion-sdk— the unified AGI Harness.
Description¶
Create SSH Tunnels to the operator's remote hosts and host as an MCP Server for Agentic AI!
Enterprise Readiness¶
All agents in the ecosystem inherit enterprise-grade infrastructure from scion-sdk:
| Feature | Status | Source |
|---|---|---|
| JWT/OIDC Authentication | ✅ Built-in | scion-sdk[auth] — Authlib JWKS + API key middleware |
| OpenTelemetry Instrumentation | ✅ Built-in | scion-sdk[logfire] — OTLP export, FastAPI auto-instrumentation |
| HashiCorp Vault Integration | ✅ Built-in | scion-sdk[vault] — secret://, env://, vault:// URI schemes |
| Audit Logging | ✅ Built-in | Append-only compliance trail with 30+ action types (CONCEPT:AU-OS.governance.wasm-micro-agent-sandbox) |
| Token Usage Analytics | ✅ Built-in | 4-bucket tracking with budget alerting (CONCEPT:AU-OS.governance.wasm-micro-agent-sandbox) |
| Prompt Injection Defense | ✅ Built-in | 25+ pattern scanner + jailbreak taxonomy (CONCEPT:AU-OS.config.secrets-authentication) |
| Guardrail Engine | ✅ Built-in | Input/output interception with block/redact/warn (CONCEPT:AU-OS.governance.reactive-multi-axis-budget) |
| Action Execution Pipeline | ✅ Built-in | Token, cost, duration, and node transition limits Dry-run / commit / rollback phases (CONCEPT:AU-ORCH.adapter.kg-graph-materialization) |
| Resource Scheduling | ✅ Built-in | Priority queuing + preemption limits (CONCEPT:AU-OS.state.cognitive-scheduler-preemption) |
| Session Concurrency | ✅ Built-in | Enqueue/reject/interrupt/rollback (CONCEPT:AU-OS.governance.reactive-multi-axis-budget) |
Concept Registry¶
This project implements or inherits the following ecosystem concepts:
| Concept ID | Description | Source |
|---|---|---|
| TUN-1.0 | Distributed SSH/RM Swarm | tunnel-manager |
| ECO-4.1 | MCP & Universal Skills | scion-sdk (inherited) |
📖 Full Registry: See
scion-sdk/docs/overview.mdfor the complete 5-Pillar concept index.
Architecture¶
The tunnel-manager functions as the "Agentless Execution Arm" for the Agent OS Kernel. When an agent needs to run commands or send/receive files across multiple remote systems without deploying persistent daemons, tunnel-manager bridges the gap.
TUN-1.0: Distributed SSH Swarm Scaling¶
To scale remote execution to 10,000+ hosts over SSH without facing catastrophic O(N) latency bottlenecks, tunnel-manager use a Parallel SSH Sub-Agent Dispatch architecture:
- Async Connection Pools: Instead of linear loops,
tunnel-managerusesasyncsshandasyncio.gatherto run batches of 1,000 SSH connections concurrently. - Dynamic Inventory Resolution: The target hosts can be dynamically queried from Cloud Providers (AWS/GCP tags) or existing CMDBs (ServiceNow), mapping smoothly into the Agent's Knowledge Graph.
- Payload MapReduce: Similar to the
systems-managerdaemon architecture, runningcat /etc/os-releaseacross 10,000 hosts will overflow the LLM's context. Thetunnel-managerMCP intercepts the 10,000 standard output strings and reduces them into a unified summary payload (e.g., "9,500 hosts are Ubuntu 24.04, 500 hosts are RHEL 9") before returning to the Agent.
This design guarantees that tunnel-manager remains purely agentless and strictly SSH-based, while achieving enterprise-grade horizontal scaling capabilities.
This project follows the standardized agent-package pattern:
tunnel-manager/
├── tunnel_manager/ # Source code
│ ├── __init__.py
│ ├── agent_server.py # Entry point (create_graph_agent_server)
│ ├── api_client.py # REST/GraphQL API wrapper
│ └── mcp_server.py # FastMCP tool definitions
├── tests/ # Test suite
├── docs/ # Documentation
├── pyproject.toml # Package metadata
├── mcp_config.json # MCP server configuration
├── main_agent.json # Agent identity & system prompt
└── Dockerfile # Container deployment
MCP Configuration¶
stdio Mode¶
{
"mcpServers": {
"tunnel-manager": {
"command": "uv",
"args": ["run", "--with", "tunnel-manager", "tunnel-mcp"],
"env": {}
}
}
}