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Systems Manager

Systems Manager

CLI or API | MCP | Agent

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Version: 1.35.0

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


Related MCP server: allcanuse-mcp

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.


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.


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.


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.


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.


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.


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.


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


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.


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.


Repository Owners

GitHub followers GitHub User's stars


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.

A
license - permissive license
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
3dRelease cycle
93Releases (12mo)
Commit activity

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