Systems Manager
CLI or API | MCP | Agent
Version: 1.22.0
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 asget_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
| Tool Module | Toggle Env Var | Enabled by Default | Description & Nested Methods |
|---|---|---|---|
| Misc | MISCTOOL |
True |
Manage misc operations. |
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
--toolsor--toolsets(or their disabled counterparts--disabled-toolsand--disabled-toolsets) during startup. - Environment Variables: Define standard environment variables:
MCP_ENABLED_TOOLS/MCP_DISABLED_TOOLSMCP_ENABLED_TAGS/MCP_DISABLED_TAGS
- HTTP SSE Request Headers: Pass custom headers during transport initialization:
x-mcp-enabled-tools/x-mcp-disabled-toolsx-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
stdio Transport (Recommended for local IDEs e.g., Cursor, Claude Desktop)
Configure your IDE's mcp.json to launch the MCP server via uvx:
{
"mcpServers": {
"systems-manager": {
"command": "uvx",
"args": [
"--from",
"systems-manager",
"systems-manager-mcp"
],
"env": {
"SYSTEMS_API_KEY": "your_systems_api_key_here"
}
}
}
}
Streamable-HTTP Transport (Recommended for production deployments)
Configure your client's mcp.json to launch the Streamable-HTTP server via uvx with explicit host and port definition:
{
"mcpServers": {
"systems-manager": {
"command": "uvx",
"args": [
"--from",
"systems-manager",
"systems-manager-mcp"
],
"env": {
"TRANSPORT": "streamable-http",
"HOST": "0.0.0.0",
"PORT": "8000",
"SYSTEMS_API_KEY": "your_systems_api_key_here"
}
}
}
}
Alternatively, connect to a pre-deployed remote or local Streamable-HTTP instance:
{
"mcpServers": {
"systems-manager": {
"url": "http://localhost:8000/systems-manager/mcp"
}
}
}
Deploying the Streamable-HTTP server via Docker:
docker run -d \
--name systems-manager-mcp \
-p 8000:8000 \
-e TRANSPORT=streamable-http \
-e PORT=8000 \
-e SYSTEMS_API_KEY="your_value" \
knucklessg1/systems-manager:latest
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 SYSTEMS_API_KEY="your_value"
# 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:latest
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, localembedded(mcp_policies.json), or centralizedremotemodes. - 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
Install the Python package locally:
# Using uv (highly recommended)
uv pip install systems-manager[all]
# Using standard pip
python -m pip install systems-manager[all]
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