tunnel-manager 2.0.1

Create SSH Tunnels to your remote hosts and host as an MCP Server for Agentic AI!

Tunnel Manager

CLI or API | MCP | Agent

Version: 2.0.1

Documentation — Installation, deployment, usage across the API, CLI, and MCP and agent interfaces are maintained in the official documentation.

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Overview

Tunnel Manager is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with Create SSH Tunnels to your remote hosts and host as an MCP Server for Agentic AI!.

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Key Features

• Consolidated Action-Routed MCP Tools: Minimizes token overhead and eliminates tool bloat in LLM contexts by grouping methods into optimized, togglable tool modules.
• Enterprise-Grade Security: Comprehensive support for Eunomia policies, OIDC token delegation, and granular execution context tracking.
• Integrated Graph Agent: Built-in Pydantic AI agent supporting the Agent Control Protocol (ACP) and standard Web interfaces (AG-UI).
• Native Telemetry & Tracing: Out-of-the-box OpenTelemetry exports and native Langfuse tracing.

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CLI or API

This agent wraps the Create SSH Tunnels to your remote hosts and host as an MCP Server for Agentic AI! API. You can interact with it programmatically or via its integrated execution entrypoints.

Detailed instructions on how to use the underlying API wrappers, extended schema bindings, and developer SDK references are maintained in docs/index.md.

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MCP

This server utilizes dynamic Action-Routed tools to optimize token overhead and maximize IDE compatibility.

Available MCP Tools

Auto-generated from the live MCP server — do not edit by hand.

Condensed action-routed tools (default — MCP_TOOL_MODE=condensed)

MCP Tool	Toggle Env Var	Description
tm_files	FILETOOL	Advanced file operations on remote hosts.
tm_hosts	HOSTTOOL	Manage the local host alias inventory.
tm_inventory	INVENTORYTOOL	Bulk inventory operations against YAML host groups.
tm_operations	OPERATIONSTOOL	Operation lifecycle and session management.
tm_remote	REMOTETOOL	Single-host SSH operations with shared connection params.
tm_security	SECURITYTOOL	Security scanning and compliance.
tm_system	SYSTEMTOOL	Remote system intelligence via SSH.

Verbose 1:1 API-mapped tools (MCP_TOOL_MODE=verbose or both)

6 per-operation tools — one per public API method (click to expand)

MCP Tool	Toggle Env Var	Description
tunnel_manager_add_host	HOST_MANAGERTOOL	Invoke the add_host operation.
tunnel_manager_get_host	HOST_MANAGERTOOL	Invoke the get_host operation.
tunnel_manager_list_hosts	HOST_MANAGERTOOL	Invoke the list_hosts operation.
tunnel_manager_load_inventory	HOST_MANAGERTOOL	Invoke the load_inventory operation.
tunnel_manager_remove_host	HOST_MANAGERTOOL	Invoke the remove_host operation.
tunnel_manager_save_inventory	HOST_MANAGERTOOL	Invoke the save_inventory operation.

7 action-routed tool(s) (default) · 6 verbose 1:1 tool(s). Each is enabled unless its <DOMAIN>TOOL toggle is set false; MCP_TOOL_MODE selects the surface (condensed default · verbose 1:1 · both). Auto-generated — do not edit.

Detailed tool schemas, parameter shapes, and validation constraints are preserved in docs/mcp.md.

Dynamic Tool Selection & Visibility

This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows you to restrict the set of exposed tools in order to prevent blowing up the LLM's context window.

You can configure tool filtering via multiple input channels:

• CLI Arguments: Pass --tools or --toolsets (or their disabled counterparts --disabled-tools and --disabled-toolsets) during startup.
• Environment Variables: Define standard environment variables:
  • MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS
  • MCP_ENABLED_TAGS / MCP_DISABLED_TAGS
• HTTP SSE Request Headers: Pass custom headers during transport initialization:
  • x-mcp-enabled-tools / x-mcp-disabled-tools
  • x-mcp-enabled-tags / x-mcp-disabled-tags
• HTTP SSE Request Query Parameters: Append query parameters directly to your transport connection URL:
  • ?tools=tool1,tool2
  • ?tags=tag1

When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.

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MCP Configuration Examples

Install the slim [mcp] extra. All examples install tunnel-manager[mcp] — the MCP-server extra that pulls only the FastMCP / FastAPI tooling (agent-utilities[mcp]). It deliberately excludes the heavy agent runtime (pydantic-ai, the epistemic-graph engine, dspy, llama-index), so uvx / container installs are far smaller. Use the full [agent] extra only when you need the integrated Pydantic AI agent.

stdio Transport (local IDEs — Cursor, Claude Desktop, VS Code)

{
  "mcpServers": {
    "tunnel-manager-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "tunnel-manager[mcp]",
        "tunnel-manager-mcp"
      ],
      "env": {
        "MCP_TOOL_MODE": "condensed",
        "FILETOOL": "True",
        "HOSTTOOL": "True",
        "INVENTORYTOOL": "True",
        "OPERATIONSTOOL": "True",
        "REMOTETOOL": "True",
        "SECURITYTOOL": "True",
        "SYSTEMTOOL": "True",
        "TUNNEL_CERTIFICATE": "",
        "TUNNEL_IDENTITY_FILE": "~/.ssh/id_ed25519",
        "TUNNEL_INVENTORY": "",
        "TUNNEL_INVENTORY_GROUP": "all",
        "TUNNEL_MAX_THREADS": "6",
        "TUNNEL_PARALLEL": "False",
        "TUNNEL_PASSWORD": "",
        "TUNNEL_PROXY_COMMAND": "",
        "TUNNEL_REMOTE_HOST": "",
        "TUNNEL_REMOTE_PORT": "22",
        "TUNNEL_USERNAME": "",
        "XDG_CONFIG_HOME": ""
      }
    }
  }
}

Streamable-HTTP Transport (networked / production)

{
  "mcpServers": {
    "tunnel-manager-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "tunnel-manager[mcp]",
        "tunnel-manager-mcp",
        "--transport",
        "streamable-http",
        "--port",
        "8000"
      ],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "0.0.0.0",
        "PORT": "8000",
        "MCP_TOOL_MODE": "condensed",
        "FILETOOL": "True",
        "HOSTTOOL": "True",
        "INVENTORYTOOL": "True",
        "OPERATIONSTOOL": "True",
        "REMOTETOOL": "True",
        "SECURITYTOOL": "True",
        "SYSTEMTOOL": "True",
        "TUNNEL_CERTIFICATE": "",
        "TUNNEL_IDENTITY_FILE": "~/.ssh/id_ed25519",
        "TUNNEL_INVENTORY": "",
        "TUNNEL_INVENTORY_GROUP": "all",
        "TUNNEL_MAX_THREADS": "6",
        "TUNNEL_PARALLEL": "False",
        "TUNNEL_PASSWORD": "",
        "TUNNEL_PROXY_COMMAND": "",
        "TUNNEL_REMOTE_HOST": "",
        "TUNNEL_REMOTE_PORT": "22",
        "TUNNEL_USERNAME": "",
        "XDG_CONFIG_HOME": ""
      }
    }
  }
}

Alternatively, connect to a pre-deployed Streamable-HTTP instance by url:

{
  "mcpServers": {
    "tunnel-manager-mcp": {
      "url": "http://localhost:8000/tunnel-manager-mcp/mcp"
    }
  }
}

Deploying the Streamable-HTTP server via Docker:

docker run -d \
  --name tunnel-manager-mcp-mcp \
  -p 8000:8000 \
  -e TRANSPORT=streamable-http \
  -e HOST=0.0.0.0 \
  -e PORT=8000 \
  -e MCP_TOOL_MODE=condensed \
  -e FILETOOL=True \
  -e HOSTTOOL=True \
  -e INVENTORYTOOL=True \
  -e OPERATIONSTOOL=True \
  -e REMOTETOOL=True \
  -e SECURITYTOOL=True \
  -e SYSTEMTOOL=True \
  -e TUNNEL_CERTIFICATE="" \
  -e TUNNEL_IDENTITY_FILE=~/.ssh/id_ed25519 \
  -e TUNNEL_INVENTORY="" \
  -e TUNNEL_INVENTORY_GROUP=all \
  -e TUNNEL_MAX_THREADS=6 \
  -e TUNNEL_PARALLEL=False \
  -e TUNNEL_PASSWORD="" \
  -e TUNNEL_PROXY_COMMAND="" \
  -e TUNNEL_REMOTE_HOST="" \
  -e TUNNEL_REMOTE_PORT=22 \
  -e TUNNEL_USERNAME="" \
  -e XDG_CONFIG_HOME="" \
  knucklessg1/tunnel-manager:mcp

Auto-generated from the code-read env surface (MCP_TOOL_MODE + package vars) — do not edit.

Additional Deployment Options

tunnel-manager can also run as a local container (Docker / Podman / uv) or be consumed from a remote deployment. The Deployment guide has full, copy-paste mcp_config.json for all four transports — stdio, streamable-http, local container / uv, and remote URL:

• Local container / uv — launch the server from mcp_config.json via uvx, docker run, or podman run, or point at a local streamable-http container by url.
• Remote URL — connect to a server deployed behind Caddy at http://tunnel-manager-mcp.arpa/mcp using the "url" key.

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Inventory

tunnel-manager works from a single shared YAML inventory that maps short host aliases (e.g. r820) to their SSH connection details. Every ecosystem surface reads the same file — the HostManager API, the tunnel-manager CLI, the MCP server, container-manager-mcp (its cm_* host aliases), and the ssh-bootstrap skill — so you define your fleet once.

• Location — ~/.config/agent-utilities/inventory.yml (.yml preferred). A legacy inventory.yaml at the same path is still read when no .yml exists, so existing installs keep working. Override with TUNNEL_INVENTORY.

• Manage it with the inventory subcommand:

  tunnel-manager inventory init     # write a commented inventory.yml template (--force to overwrite)
  tunnel-manager inventory doctor   # validate hosts/groups; --fix migrates legacy .yaml -> .yml
  tunnel-manager inventory show     # print the resolved path + host/group summary
  

Full schema, every host field, the copy-paste template, and override options live in the Inventory guide.

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Environment Variables

Package environment variables

Variable	Example	Description
HOST	0.0.0.0
PORT	8000
TRANSPORT	stdio	options: stdio, streamable-http, sse
ENABLE_OTEL	True
OTEL_EXPORTER_OTLP_ENDPOINT	http://localhost:8080/api/public/otel
OTEL_EXPORTER_OTLP_PUBLIC_KEY	pk-...
OTEL_EXPORTER_OTLP_SECRET_KEY	sk-...
OTEL_EXPORTER_OTLP_PROTOCOL	http/protobuf
EUNOMIA_TYPE	none	options: none, embedded, remote
EUNOMIA_POLICY_FILE	mcp_policies.json
EUNOMIA_REMOTE_URL	http://eunomia-server:8000
TUNNEL_IDENTITY_FILE	~/.ssh/id_ed25519
DEBUG	False
PYTHONUNBUFFERED	1
TUNNEL_REMOTE_HOST	—	default remote host (e.g. 192.168.1.10)
TUNNEL_REMOTE_PORT	22	default SSH port
TUNNEL_USERNAME	—	default SSH username
TUNNEL_PASSWORD	—	default SSH password (prefer key-based auth)
TUNNEL_CERTIFICATE	—	path to an SSH certificate file
TUNNEL_PROXY_COMMAND	—	SSH ProxyCommand for jump-host/bastion connections
TUNNEL_INVENTORY	—	path to the inventory file (defaults to XDG config path)
TUNNEL_INVENTORY_GROUP	all	inventory host group to target
TUNNEL_PARALLEL	False	run host operations in parallel
TUNNEL_MAX_THREADS	6	max worker threads when TUNNEL_PARALLEL=True
XDG_CONFIG_HOME	—	base config dir (defaults to ~/.config) for inventory resolution
HOSTTOOL	True	Grouped condensed-surface toggles, one per register__tools registrar.
REMOTETOOL	True
INVENTORYTOOL	True
OPERATIONSTOOL	True
SYSTEMTOOL	True
FILETOOL	True
SECURITYTOOL	True

Inherited agent-utilities variables (apply to every connector)

Variable	Example	Description
MCP_TOOL_MODE	condensed	Tool surface: condensed
MCP_ENABLED_TOOLS	—	Comma-separated tool allow-list
MCP_DISABLED_TOOLS	—	Comma-separated tool deny-list
MCP_ENABLED_TAGS	—	Comma-separated tag allow-list
MCP_DISABLED_TAGS	—	Comma-separated tag deny-list
MCP_CLIENT_AUTH	—	Outbound MCP auth (oidc-client-credentials for fleet calls)
OIDC_CLIENT_ID	—	OIDC client id (service-account auth)
OIDC_CLIENT_SECRET	—	OIDC client secret (service-account auth)
MCP_URL	http://localhost:8000/mcp	URL of the MCP server the agent connects to
PROVIDER	openai	LLM provider for the agent
MODEL_ID	gpt-4o	Model id for the agent
ENABLE_WEB_UI	True	Serve the AG-UI web interface

32 package + 12 inherited variable(s). Auto-generated from .env.example + the shared agent-utilities set — do not edit.

Every variable the server reads, grouped by purpose. See .env.example for a copy-paste starting point.

SSH connection & credentials

Variable	Description	Default
TUNNEL_IDENTITY_FILE	Path to the SSH private key	~/.ssh/id_ed25519
TUNNEL_USERNAME	SSH username	—
TUNNEL_PASSWORD	SSH password (when not using a key)	—
TUNNEL_CERTIFICATE	Path to an SSH certificate	—
TUNNEL_REMOTE_HOST	Default remote host	—
TUNNEL_REMOTE_PORT	Default remote SSH port	22
TUNNEL_PROXY_COMMAND	SSH ProxyCommand for jump hosts	—

Inventory & parallelism

Variable	Description	Default
TUNNEL_INVENTORY	Path to the shared inventory (.yml preferred, .yaml legacy fallback)	~/.config/agent-utilities/inventory.yml
TUNNEL_INVENTORY_GROUP	Default inventory host group	—
TUNNEL_PARALLEL	Run bulk operations in parallel	—
TUNNEL_MAX_THREADS	Max concurrent SSH worker threads	—
XDG_CONFIG_HOME	Base config dir used to resolve the inventory	~/.config

MCP server / transport

Variable	Description	Default
TRANSPORT	stdio, streamable-http, or sse	stdio
HOST	Bind host (HTTP transports)	0.0.0.0
PORT	Bind port (HTTP transports)	8000
MCP_TOOL_MODE	Tool surface: condensed, verbose, or both	condensed
MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS	Comma-separated tool allow/deny list	—
MCP_ENABLED_TAGS / MCP_DISABLED_TAGS	Comma-separated tag allow/deny list	—
DEBUG	Verbose logging	False
PYTHONUNBUFFERED	Unbuffered stdout (recommended in containers)	1

Tool toggles

Each action-routed tool can be disabled individually via its toggle env var (set to false). The full list is in the Available MCP Tools table above (HOSTTOOL, REMOTETOOL, INVENTORYTOOL, OPERATIONSTOOL, SYSTEMTOOL, FILETOOL, SECURITYTOOL).

Telemetry & governance

Variable	Description	Default
ENABLE_OTEL	Enable OpenTelemetry export	True
OTEL_EXPORTER_OTLP_ENDPOINT	OTLP collector endpoint	—
OTEL_EXPORTER_OTLP_PUBLIC_KEY / OTEL_EXPORTER_OTLP_SECRET_KEY	OTLP auth keys	—
OTEL_EXPORTER_OTLP_PROTOCOL	OTLP protocol (e.g. http/protobuf)	—
EUNOMIA_TYPE	Authorization mode: none, embedded, remote	none
EUNOMIA_POLICY_FILE	Embedded policy file	mcp_policies.json
EUNOMIA_REMOTE_URL	Remote Eunomia server URL	—

Agent runtime (full [agent] runtime only)

Variable	Description	Default
MCP_URL	URL of the MCP server the agent connects to	http://localhost:8000/mcp
PROVIDER	LLM provider (e.g. openai)	openai
MODEL_ID	Model id (e.g. gpt-4o)	gpt-4o
ENABLE_WEB_UI	Serve the AG-UI web interface	True

Agent

This repository features a fully integrated Pydantic AI Graph Agent. It communicates over the Agent Control Protocol (ACP) and interacts seamlessly with the Agent Web UI (AG-UI) and Terminal interface.

Running the Agent CLI

To start the interactive command-line agent:

# Set credentials
export TUNNEL_IDENTITY_FILE="your_value"
export DEBUG="your_value"
export PYTHONUNBUFFERED="your_value"

# Run the agent server
tunnel-manager-agent --provider openai --model-id gpt-4o

Docker Compose Orchestration

The following docker/agent.compose.yml configures the Agent, Web UI, and Terminal Interface together:

version: '3.8'

services:
  tunnel-manager-mcp:
    image: knucklessg1/tunnel-manager:mcp
    container_name: tunnel-manager-mcp
    hostname: tunnel-manager-mcp
    restart: always
    env_file:
      - ../.env
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=streamable-http
    ports:
      - "8000:8000"
    healthcheck:
      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s
    logging:
      driver: json-file
      options:
        max-size: "10m"
        max-file: "3"

  tunnel-manager-agent:
    image: knucklessg1/tunnel-manager:latest
    container_name: tunnel-manager-agent
    hostname: tunnel-manager-agent
    restart: always
    depends_on:
      - tunnel-manager-mcp
    env_file:
      - ../.env
    command: [ "tunnel-manager-agent" ]
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=9002
      - MCP_URL=http://tunnel-manager-mcp:8000/mcp
      - PROVIDER=${PROVIDER:-openai}
      - MODEL_ID=${MODEL_ID:-gpt-4o}
      - ENABLE_WEB_UI=True
      - ENABLE_OTEL=True
    ports:
      - "9002:9002"
    healthcheck:
      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9002/health')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s
    logging:
      driver: json-file
      options:
        max-size: "10m"
        max-file: "3"

Detailed graph node architecture explanations, custom skill configurations, and agentic trace guides are available in docs/agent.md.

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Security & Governance

Built directly upon the enterprise-ready agent-utilities core, standard security parameters are fully supported:

Access Control & Policy Enforcement

• Eunomia Policies: Fine-grained, policy-driven tool authorization. Supports none, local embedded (mcp_policies.json), or centralized remote modes.
• OIDC Token Delegation: Compliant with RFC 8693 token exchange for flowing authenticating user credentials from Web UI / ACP → Agent → MCP.
• Scoped Credentials: Execution context runs restricted to the specific caller identity.

Runtime Security Grid

Feature	Functionality	Enablement
Tool Guard	Sensitivity inspection with human-in-the-loop validation	Enabled by default
Prompt Injection Defense	Input scanning, repetition monitoring, and recursive loop blocks	Enabled by default
Context Safety Guard	Stuck-loop detectors and contextual overflow preemptive alerts	Enabled by default

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Installation

Pick the extra that matches what you want to run:

Extra	Installs	Use when
tunnel-manager[mcp]	Slim MCP server only (agent-utilities[mcp] — FastMCP/FastAPI)	You only run the MCP server (smallest install / image)
tunnel-manager[agent]	Full agent runtime (agent-utilities[agent,logfire] — Pydantic AI + the epistemic-graph engine)	You run the integrated agent
tunnel-manager[all]	Everything (mcp + agent + logfire)	Development / both surfaces

# MCP server only (recommended for tool hosting — slim deps)
uv pip install "tunnel-manager[mcp]"

# Full agent runtime (Pydantic AI + epistemic-graph engine)
uv pip install "tunnel-manager[agent]"

# Everything (development)
uv pip install "tunnel-manager[all]"      # or: python -m pip install "tunnel-manager[all]"

Container images (:mcp vs :agent)

One multi-stage docker/Dockerfile builds two right-sized images, selected by --target:

Image tag	Build target	Contents	Entrypoint
knucklessg1/tunnel-manager:mcp	--target mcp	tunnel-manager[mcp] — slim, no engine/pydantic-ai/dspy/llama-index/tree-sitter	tunnel-manager-mcp
knucklessg1/tunnel-manager:latest	--target agent (default)	tunnel-manager[agent] — full agent runtime + epistemic-graph engine	tunnel-manager-agent

docker build --target mcp   -t knucklessg1/tunnel-manager:mcp    docker/   # slim MCP server
docker build --target agent -t knucklessg1/tunnel-manager:latest docker/   # full agent

docker/mcp.compose.yml runs the slim :mcp server; docker/agent.compose.yml runs the agent (:latest) with a co-located :mcp sidecar.

Knowledge-graph database (epistemic-graph)

The full agent ([agent] / :latest) embeds the epistemic-graph engine (pulled in transitively via agent-utilities[agent]). For production — or to share one knowledge graph across multiple agents — run epistemic-graph as its own database container and point the agent at it instead of embedding it. Deployment recipes (single-node + Raft HA), connection config, and the full database architecture (with diagrams) are documented in the epistemic-graph deployment guide. The slim [mcp] server does not require the database.

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Documentation

The complete documentation is published as the official documentation site and is the recommended reference for installation, deployment, and day-to-day operation.

Page	Contents
Installation	pip, source, extras, prebuilt Docker image
Inventory	the shared inventory.yaml — default location, how to create it, formats, overrides
Deployment	run the MCP and agent servers, Compose, Caddy + Technitium, env config
Usage	the MCP tools, the HostManager / Tunnel API, the CLI
Overview	ecosystem role, distributed SSH swarm scaling, MCP configuration
Teleport Architecture	certificate, proxy and cross-OS connection model
Concepts	concept registry (CONCEPT:TUN-*)

AGENTS.md is the canonical contributor/agent guidance.

Repository Owners

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Contribute

Contributions are welcome! Please ensure code quality by executing local checks before submitting pull requests:

• Format code using ruff format .
• Lint code using ruff check .
• Validate type-safety with mypy .
• Execute test suites using pytest

Deploy with agent-os-genesis

This package can be provisioned for you — skill-guided — by the agent-os-genesis universal skill (its single-package deploy mode): it picks your install method, seeds secrets to OpenBao/Vault (or .env), trusts your enterprise CA, registers the MCP server, and verifies it — the same machinery that stands up the whole Agent OS, narrowed to just this package. Ask your agent to "deploy tunnel-manager with agent-os-genesis".

Install mode	Command
Bare-metal, prod (PyPI)	uvx tunnel-manager-mcp · or uv tool install tunnel-manager
Bare-metal, dev (editable)	uv pip install -e ".[all]" · or pip install -e ".[all]"
Container, prod	deploy knucklessg1/tunnel-manager:latest via docker-compose / swarm / podman / podman-compose / kubernetes
Container, dev (editable)	deploy docker/compose.dev.yml (source-mounted at /src; edits live on restart)

Secrets are read-existing + seeded via vault_sync — you are only prompted for what's missing.