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.

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

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.

Name		Name	Last commit message	Last commit date
Latest commit History 346 Commits
.github/workflows		.github/workflows
.specify/specs		.specify/specs
docker		docker
docs		docs
scripts		scripts
specify_reports/systems-manager		specify_reports/systems-manager
systems_manager		systems_manager
tests		tests
.bumpversion.cfg		.bumpversion.cfg
.codespellignore		.codespellignore
.dockerignore		.dockerignore
.env.example		.env.example
.gitattributes		.gitattributes
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
AGENTS.md		AGENTS.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
README.md		README.md
a2a.json		a2a.json
mcp_config.json		mcp_config.json
mkdocs.yml		mkdocs.yml
opencode.json		opencode.json
pyproject.toml		pyproject.toml
pytest.ini		pytest.ini
requirements.txt		requirements.txt
uv.lock		uv.lock

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Systems Manager

CLI or API | MCP | Agent

Overview

Key Features

Multi-Host & Zero-Script Remote Orchestration

CLI or API

MCP

Available MCP Tools

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

Dynamic Tool Selection & Visibility

MCP Configuration Examples

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

Streamable-HTTP Transport (networked / production)

Additional Deployment Options

Environment Variables

Package environment variables

Inherited agent-utilities variables (apply to every connector)

MCP server / transport

Connection & credentials

Multi-host remote orchestration

Tool toggles

Telemetry & governance

Agent runtime governance (full [agent] runtime only)

Agent

Running the Agent CLI

Docker Compose Orchestration

Security & Governance

Access Control & Policy Enforcement

Runtime Security Grid

Installation

Container images (:mcp vs :agent)

Knowledge-graph database (epistemic-graph)

Documentation

Repository Owners

Contribute

Deploy with agent-os-genesis

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

Agent runtime governance (full `[agent]` runtime only)

Container images (`:mcp` vs `:agent`)

Knowledge-graph database (`epistemic-graph`)

Deploy with `agent-os-genesis`

Packages