systems-manager 1.35.1

Systems Manager will update your system and install/upgrade applications. Additionally, as allow AI to perform these activities as an MCP Server

Systems Manager

CLI or API | MCP | Agent

Version: 1.35.0

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

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Overview

Systems Manager is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with Systems Manager will update your system and install/upgrade applications. Additionally, as allow AI to perform these activities as an MCP Server.

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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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Multi-Host & Zero-Script Remote Orchestration

systems-manager supports full zero-script remote server telemetry and control plane routing out of the box.

• Unified Inventory: Single source of truth inventory loaded dynamically from standard XDG paths (~/.config/agent_utilities/inventory.yaml).
• Zero Remote Dependencies: Remote targets require only standard SSH access and a standard Python interpreter—no remote daemons, systemd configurations, or software packages are deployed on the target hosts.
• Dynamic Telemetry Serialization (remote_eval): Telemetries (such as get_os_statistics(), get_hardware_statistics(), and process monitoring) are automatically packed and evaluated dynamically over secure SSH tunnels.

To configure and utilize the multi-host remote routing, see the detailed Multi-Host Architecture Guide.

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CLI or API

This agent wraps the Systems Manager will update your system and install/upgrade applications. Additionally, as allow AI to perform these activities as an MCP Server 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
capture_system_snapshot	OS_PROVIDERTOOL	Takes a point-in-time snapshot of the system state (CPU, RAM, Processes).
get_network_connections	OS_PROVIDERTOOL	Maps active TCP/UDP endpoints directly to owning processes.
get_process_details	OS_PROVIDERTOOL	Retrieves deep cross-platform process details (threads, modules, memory).
health_check	—
list_kernel_modules	OS_PROVIDERTOOL	List loaded drivers/modules (lsmod or driverquery).
list_services	OS_PROVIDERTOOL	Cross-platform service enumeration (systemctl or Get-Service).
manage_service	OS_PROVIDERTOOL	Start/Stop/Restart/Enable/Disable services cross-platform.
query_system_logs	OS_PROVIDERTOOL	Cross-platform log querying (journalctl or Get-WinEvent).
sm_advanced_operations	—	Operations for SSH and specialized managers
sm_cron_operations	—	Operations for cron jobs
sm_disk_operations	—	Operations for managing system disks
sm_file_operations	—	Operations for file and log management
sm_firewall_operations	—	Operations for firewall management
sm_network_operations	—	Operations for network analysis
sm_process_operations	—	Operations for managing system processes
sm_service_operations	—	Operations for managing system services
sm_storage_health	STORAGE_HEALTHTOOL	Physical disk + BMC drive-fault health: SMART (incl. RAID megaraid passthrough), BMC/IPMI drive-slot faults (OpenBao-credentialed OOB), RAID PD state — correlated.
sm_system_operations	—	System operations for managing packages, system health, and updates
sm_user_operations	—	Operations for user and group management
start_system_trace	OS_PROVIDERTOOL	Start a kernel-level event trace (ETW on Windows, or strace on Linux).
stop_system_trace	OS_PROVIDERTOOL	Stop a kernel-level event trace.

20 action-routed tool(s) (default) · 0 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 systems-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": {
    "systems-manager-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "systems-manager[mcp]",
        "systems-manager-mcp"
      ],
      "env": {
        "MCP_TOOL_MODE": "condensed",
        "AGENT_HEALTHTOOL": "True",
        "AGENT_POLICIES_PATH": "",
        "IDENTITYTOOL": "True",
        "MAINTENANCETOOL": "True",
        "MAINTENANCE_PRIORITY": "",
        "MAINTENANCE_TOKEN_BUDGET": "",
        "MAX_CONCURRENT_AGENTS": "",
        "MCP_CONFIG_PATH": "",
        "MISCTOOL": "True",
        "OPENBAO_TOKEN": "",
        "OPENBAO_URL": "http://openbao.arpa",
        "OS_PROVIDERTOOL": "True",
        "PERMISSIONS_SIGNING_KEY": "",
        "POLICYTOOL": "True",
        "PROJECT_ROOT": "",
        "SPECIALIST_REGISTRYTOOL": "True",
        "SPECIALIST_REGISTRY_PATH": "",
        "STORAGE_HEALTHTOOL": "True",
        "SYSTEMS_MANAGER_HOST": "",
        "WATCHDOGTOOL": "True"
      }
    }
  }
}

Streamable-HTTP Transport (networked / production)

{
  "mcpServers": {
    "systems-manager-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "systems-manager[mcp]",
        "systems-manager-mcp",
        "--transport",
        "streamable-http",
        "--port",
        "8000"
      ],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "0.0.0.0",
        "PORT": "8000",
        "MCP_TOOL_MODE": "condensed",
        "AGENT_HEALTHTOOL": "True",
        "AGENT_POLICIES_PATH": "",
        "IDENTITYTOOL": "True",
        "MAINTENANCETOOL": "True",
        "MAINTENANCE_PRIORITY": "",
        "MAINTENANCE_TOKEN_BUDGET": "",
        "MAX_CONCURRENT_AGENTS": "",
        "MCP_CONFIG_PATH": "",
        "MISCTOOL": "True",
        "OPENBAO_TOKEN": "",
        "OPENBAO_URL": "http://openbao.arpa",
        "OS_PROVIDERTOOL": "True",
        "PERMISSIONS_SIGNING_KEY": "",
        "POLICYTOOL": "True",
        "PROJECT_ROOT": "",
        "SPECIALIST_REGISTRYTOOL": "True",
        "SPECIALIST_REGISTRY_PATH": "",
        "STORAGE_HEALTHTOOL": "True",
        "SYSTEMS_MANAGER_HOST": "",
        "WATCHDOGTOOL": "True"
      }
    }
  }
}

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

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

Deploying the Streamable-HTTP server via Docker:

docker run -d \
  --name systems-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 AGENT_HEALTHTOOL=True \
  -e AGENT_POLICIES_PATH="" \
  -e IDENTITYTOOL=True \
  -e MAINTENANCETOOL=True \
  -e MAINTENANCE_PRIORITY="" \
  -e MAINTENANCE_TOKEN_BUDGET="" \
  -e MAX_CONCURRENT_AGENTS="" \
  -e MCP_CONFIG_PATH="" \
  -e MISCTOOL=True \
  -e OPENBAO_TOKEN="" \
  -e OPENBAO_URL=http://openbao.arpa \
  -e OS_PROVIDERTOOL=True \
  -e PERMISSIONS_SIGNING_KEY="" \
  -e POLICYTOOL=True \
  -e PROJECT_ROOT="" \
  -e SPECIALIST_REGISTRYTOOL=True \
  -e SPECIALIST_REGISTRY_PATH="" \
  -e STORAGE_HEALTHTOOL=True \
  -e SYSTEMS_MANAGER_HOST="" \
  -e WATCHDOGTOOL=True \
  knucklessg1/systems-manager:mcp

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

Additional Deployment Options

systems-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://systems-manager-mcp.arpa/mcp using the "url" key.

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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
SYSTEMS_MANAGER_HOST	—	target host for remote telemetry/control (defaults to local)
PROJECT_ROOT	—	project root used to resolve config/inventory paths
MCP_CONFIG_PATH	—	path to the MCP config (mcp_config.json)
MAX_CONCURRENT_AGENTS	—	cap on concurrently dispatched sub-agents
MAINTENANCE_PRIORITY	—	maintenance-lane scheduling priority
MAINTENANCE_TOKEN_BUDGET	—	maintenance-lane token budget
AGENT_POLICIES_PATH	—	path to agent authorization policies
PERMISSIONS_SIGNING_KEY	—	signing key for elevated-permission tokens
SPECIALIST_REGISTRY_PATH	—	path to the specialist/domain registry
OPENBAO_URL	http://openbao.arpa	OpenBao address for out-of-band BMC creds (apps/idrac)
OPENBAO_TOKEN	—	OpenBao token with read on apps/data/idrac (agent-apps-rw)
OS_PROVIDERTOOL	True	MCP tools table (condensed action-routed surface).
STORAGE_HEALTHTOOL	True
MISCTOOL	True
AGENT_HEALTHTOOL	True
IDENTITYTOOL	True
MAINTENANCETOOL	True
POLICYTOOL	True
SPECIALIST_REGISTRYTOOL	True
WATCHDOGTOOL	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)
DEBUG	False	Verbose logging
PYTHONUNBUFFERED	1	Unbuffered stdout (recommended in containers)
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

28 package + 14 inherited variable(s). Auto-generated from .env.example + the shared agent-utilities set — do not edit.

Every variable the server reads, grouped by purpose.

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

Connection & credentials

Variable	Description	Default
SYSTEMS_MANAGER_HOST	Target host for remote telemetry/control (defaults to local)	—

Multi-host remote orchestration

Variable	Description	Default
PROJECT_ROOT	Project root used to resolve config/inventory paths	—
MCP_CONFIG_PATH	Path to the MCP config (mcp_config.json)	—

The remote inventory is loaded from ~/.config/agent_utilities/inventory.yaml (XDG path); see the Multi-Host Architecture Guide.

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 (e.g. OS_PROVIDERTOOL, MISCTOOL).

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 governance (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
MAX_CONCURRENT_AGENTS	Cap on concurrently dispatched sub-agents	—
MAINTENANCE_PRIORITY / MAINTENANCE_TOKEN_BUDGET	Maintenance-lane scheduling controls	—
AGENT_POLICIES_PATH	Path to agent authorization policies	—
PERMISSIONS_SIGNING_KEY	Signing key for elevated-permission tokens	—
SPECIALIST_REGISTRY_PATH	Path to the specialist/domain registry	—

See .env.example for a copy-paste starting point.

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:

# Optional: target a remote host for telemetry/control
export SYSTEMS_MANAGER_HOST="remote-host.local"

# Run the agent server
systems-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:
  systems-manager-mcp:
    image: knucklessg1/systems-manager:mcp
    container_name: systems-manager-mcp
    hostname: systems-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"

  systems-manager-agent:
    image: knucklessg1/systems-manager:latest
    container_name: systems-manager-agent
    hostname: systems-manager-agent
    restart: always
    depends_on:
      - systems-manager-mcp
    env_file:
      - ../.env
    command: [ "systems-manager-agent" ]
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=9009
      - MCP_URL=http://systems-manager-mcp:8000/mcp
      - PROVIDER=${PROVIDER:-openai}
      - MODEL_ID=${MODEL_ID:-gpt-4o}
      - ENABLE_WEB_UI=True
      - ENABLE_OTEL=True
    ports:
      - "9009:9009"
    healthcheck:
      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9009/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
systems-manager[mcp]	Slim MCP server only (agent-utilities[mcp] — FastMCP/FastAPI)	You only run the MCP server (smallest install / image)
systems-manager[agent]	Full agent runtime (agent-utilities[agent,logfire] — Pydantic AI + the epistemic-graph engine)	You run the integrated agent
systems-manager[all]	Everything (mcp + agent + logfire)	Development / both surfaces

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

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

# Everything (development)
uv pip install "systems-manager[all]"      # or: python -m pip install "systems-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/systems-manager:mcp	--target mcp	systems-manager[mcp] — slim, no engine/pydantic-ai/dspy/llama-index/tree-sitter	systems-manager-mcp
knucklessg1/systems-manager:latest	--target agent (default)	systems-manager[agent] — full agent runtime + epistemic-graph engine	systems-manager-agent

docker build --target mcp   -t knucklessg1/systems-manager:mcp    docker/   # slim MCP server
docker build --target agent -t knucklessg1/systems-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
Deployment	run the MCP and agent servers, Compose, Caddy + Technitium, env config
Usage	the MCP tools, the SystemsManager API, the CLI
Overview	ecosystem role and concept map
Sudo Security	least-privilege elevated-execution model
Multi-Host	zero-script remote telemetry and control plane
Day 0 Installation	bare-metal to managed cluster node

AGENTS.md is the canonical contributor/agent guidance.

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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 systems-manager with agent-os-genesis".

Install mode	Command
Bare-metal, prod (PyPI)	uvx systems-manager-mcp · or uv tool install systems-manager
Bare-metal, dev (editable)	uv pip install -e ".[all]" · or pip install -e ".[all]"
Container, prod	deploy knucklessg1/systems-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.