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<h1>Glances</h1>

An Eye on your System

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Summary 🌟

Glances is an open-source system cross-platform monitoring tool. It allows real-time monitoring of various aspects of your system such as CPU, memory, disk, network usage etc. It also allows monitoring of running processes, logged in users, temperatures, voltages, fan speeds etc. It also supports container monitoring, it supports different container management systems such as Docker, LXC. The information is presented in an easy to read dashboard and can also be used for remote monitoring of systems via a web interface or command line interface. It is easy to install and use and can be customized to show only the information that you are interested in.

In client/server mode, remote monitoring could be done via terminal, Web interface or API (XML-RPC and RESTful). Stats can also be exported to files or external time/value databases, CSV or direct output to STDOUT.

AI assistants (Claude, Cursor, …) can query Glances directly through the built-in MCP server (available in Glances 4.5.1 and higher).

Glances is written in Python and uses libraries to grab information from your system. It is based on an open architecture where developers can add new plugins or exports modules.

Usage 👋

For the standalone mode, just run:

.. code-block:: console

$ glances

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For the Web server mode, run:

.. code-block:: console

$ glances -w

and enter the URL http://<ip>:61208 in your favorite web browser.

In this mode, a HTTP/Restful API is exposed, see document RestfulApi_ for more details.

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To also expose a MCP (Model Context Protocol)_ server (for AI assistants), add --enable-mcp:

.. code-block:: console

$ glances -w --enable-mcp

The MCP endpoint (SSE transport) is then available at http://<ip>:61208/mcp/sse. See the McpApi_ documentation for client configuration and usage.

You can also detect and display all Glances servers available on your network (or defined in the configuration file) in TUI:

.. code-block:: console

$ glances --browser

or WebUI:

.. code-block:: console

$ glances -w --browser

It possible to display raw stats on stdout:

.. code-block:: console

$ glances --stdout cpu.user,mem.used,load
cpu.user: 30.7
mem.used: 3278204928
load: {'cpucore': 4, 'min1': 0.21, 'min5': 0.4, 'min15': 0.27}
cpu.user: 3.4
mem.used: 3275251712
load: {'cpucore': 4, 'min1': 0.19, 'min5': 0.39, 'min15': 0.27}
...

or in a CSV format thanks to the stdout-csv option:

.. code-block:: console

$ glances --stdout-csv now,cpu.user,mem.used,load
now,cpu.user,mem.used,load.cpucore,load.min1,load.min5,load.min15
2018-12-08 22:04:20 CEST,7.3,5948149760,4,1.04,0.99,1.04
2018-12-08 22:04:23 CEST,5.4,5949136896,4,1.04,0.99,1.04
...

or in a JSON format thanks to the stdout-json option (attribute not supported in this mode in order to have a real JSON object in output):

.. code-block:: console

$ glances --stdout-json cpu,mem
cpu: {"total": 29.0, "user": 24.7, "nice": 0.0, "system": 3.8, "idle": 71.4, "iowait": 0.0, "irq": 0.0, "softirq": 0.0, "steal": 0.0, "guest": 0.0, "guest_nice": 0.0, "time_since_update": 1, "cpucore": 4, "ctx_switches": 0, "interrupts": 0, "soft_interrupts": 0, "syscalls": 0}
mem: {"total": 7837949952, "available": 2919079936, "percent": 62.8, "used": 4918870016, "free": 2919079936, "active": 2841214976, "inactive": 3340550144, "buffers": 546799616, "cached": 3068141568, "shared": 788156416}
...

Last but not least, you can use the fetch mode to get a quick look of a machine:

.. code-block:: console

$ glances --fetch

Results look like this:

.. image:: ./docs/_static/screenshot-fetch.png

For the record, Glances also have a XML-RPC client/server mode, run the following command on the server:

.. code-block:: console

$ glances -s

and this one on the client:

.. code-block:: console

$ glances -c <ip>

Use Glances as a Python library 📚

You can access the Glances API by importing the glances.api module and creating an instance of the GlancesAPI class. This instance provides access to all Glances plugins and their fields. For example, to access the CPU plugin and its total field, you can use the following code:

.. code-block:: python

>>> from glances import api
>>> gl = api.GlancesAPI()
>>> gl.cpu
{'cpucore': 16,
 'ctx_switches': 1214157811,
 'guest': 0.0,
 'idle': 91.4,
 'interrupts': 991768733,
 'iowait': 0.3,
 'irq': 0.0,
 'nice': 0.0,
 'soft_interrupts': 423297898,
 'steal': 0.0,
 'syscalls': 0,
 'system': 5.4,
 'total': 7.3,
 'user': 3.0}
>>> gl.cpu.get("total")
7.3
>>> gl.mem.get("used")
12498582144
>>> gl.auto_unit(gl.mem.get("used"))
11.6G

If the stats return a list of items (like network interfaces or processes), you can access them by their name:

.. code-block:: python

>>> gl.network.keys()
['wlp0s20f3', 'veth33b370c', 'veth19c7711']
>>> gl.network.get("wlp0s20f3")
{'alias': None,
 'bytes_all': 362,
 'bytes_all_gauge': 9242285709,
 'bytes_all_rate_per_sec': 1032.0,
 'bytes_recv': 210,
 'bytes_recv_gauge': 7420522678,
 'bytes_recv_rate_per_sec': 599.0,
 'bytes_sent': 152,
 'bytes_sent_gauge': 1821763031,
 'bytes_sent_rate_per_sec': 433.0,
 'interface_name': 'wlp0s20f3',
 'key': 'interface_name',
 'speed': 0,
 'time_since_update': 0.3504955768585205}

For a complete example of how to use Glances as a library, have a look to the PythonApi_.

Documentation 📜

For complete documentation have a look at the readthedocs_ website.

If you have any question (after RTFM! and the FAQ), please post it on the official Reddit forum or in GitHub Discussions_.

Gateway to other services 🌐

Glances can export stats to:

files: CSV and JSON
databases: InfluxDB, ElasticSearch, PostgreSQL/TimeScale, Cassandra, ClickHouse, CouchDB, OpenTSDB, Prometheus, StatsD, Riemann and Graphite
brokers: RabbitMQ/ActiveMQ, NATS, ZeroMQ and Kafka
others: RESTful endpoint

Installation 🚀

There are several methods to test/install Glances on your system. Choose your weapon!

PyPI: Pip, the standard way

Glances is on PyPI. By using PyPI, you will be using the latest stable version.

To install Glances, simply use the pip command line in an virtual environment.

.. code-block:: console

cd ~
python3 -m venv ~/.venv
source ~/.venv/bin/activate
pip install glances

Note: Python headers are required to install psutil_, a Glances dependency. For example, on Debian/Ubuntu the simplest is apt install python3-psutil or alternatively need to install first the python-dev package and gcc (python-devel on Fedora/CentOS/RHEL). For Windows, just install psutil from the binary installation file.

By default, Glances is installed without the Web interface dependencies.

To install it, use the following command:

.. code-block:: console

pip install 'glances[web]'

For a full installation (with all features, see features list bellow):

.. code-block:: console

pip install 'glances[all]'

Features list:

all: install dependencies for all features
action: install dependencies for action feature
browser: install dependencies for Glances centram browser
cloud: install dependencies for cloud plugin
containers: install dependencies for container plugin
export: install dependencies for all exports modules
gpu: install dependencies for GPU plugin
graph: install dependencies for graph export
ip: install dependencies for IP public option
mcp: install dependencies for the MCP server (AI assistant integration)
raid: install dependencies for RAID

Glances

Install / Use

README

Summary 🌟

Usage 👋

Use Glances as a Python library 📚

Documentation 📜

Gateway to other services 🌐

Installation 🚀

PyPI: Pip, the standard way