Glances

An Eye on your System

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.

For the standalone (TUI) mode, just run:

$ glances

For the Web server mode (WebUI), run:

$ 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.

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

$ 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:

$ glances --browser

or WebUI:

$ glances -w --browser

It possible to display raw stats on stdout:

$ 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:

$ 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):

$ 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:

$ glances --fetch

Results look like this:

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

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:

>>> 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:

>>> 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.

If you do not want to remember all thoses options, @yottajunaid has created a simple launcher for Linux.

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.

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

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

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.

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:

pip install 'glances[web]'

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

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 plugin
• sensors: install dependencies for sensors plugin
• smart: install dependencies for smart plugin
• snmp: install dependencies for SNMP
• sparklines: install dependencies for sparklines option
• web: install dependencies for Webserver (WebUI) and Web API
• wifi: install dependencies for Wifi plugin

To upgrade Glances to the latest version:

pip install --upgrade glances

Install and run directly Glances with the one line:

uvx glances

Note: Uv should be installed on your system.

Install PipX on your system. For example on Ubuntu/Debian:

sudo apt install pipx

Then install Glances (with all features):

pipx install 'glances[all]'

The glances script will be installed in the ~/.local/bin folder.

To upgrade Glances to the latest version:

pipx upgrade glances

Glances Docker images are available. You can use it to monitor your server and all your containers !

The following tags are available:

• latest-full for a full Alpine Glances image (latest release) with all dependencies
• latest for a basic Alpine Glances (latest release) version with minimal dependencies (FastAPI and Docker)
• dev for a basic Alpine Glances image (based on development branch) with all dependencies (Warning: may be instable)
• ubuntu-latest-full for a full Ubuntu Glances image (latest release) with all dependencies
• ubuntu-latest for a basic Ubuntu Glances (latest release) version with minimal dependencies (FastAPI and Docker)
• ubuntu-dev for a basic Ubuntu Glances image (based on development branch) with all dependencies (Warning: may be instable)

Run last version of Glances container in console mode:

docker run --rm -e TZ="${TZ}" -v /var/run/docker.sock:/var/run/docker.sock:ro -v /run/user/1000/podman/podman.sock:/run/user/1000/podman/podman.sock:ro --pid host --network host -it nicolargo/glances:latest-full

By default, the /etc/glances/glances.conf file is used (based on docker-compose/glances.conf).

Additionally, if you want to use your own glances.conf file, you can create your own Dockerfile:

FROM nicolargo/glances:latest
COPY glances.conf /root/.config/glances/glances.conf
CMD python -m glances -C /root/.config/glances/glances.conf $GLANCES_OPT

Alternatively, you can specify something along the same lines with docker run options (notice the GLANCES_OPT environment variable setting parameters for the glances startup command):

docker run -e TZ="${TZ}" -v $HOME/.config/glances/glances.conf:/glances.conf:ro -v /var/run/docker.sock:/var/run/docker.sock:ro -v /run/user/1000/podman/podman.sock:/run/user/1000/podman/podman.sock:ro --pid host -e GLANCES_OPT="-C /glances.conf" -it nicolargo/glances:latest-full

Where $HOME/.config/glances/glances.conf is a local directory containing your glances.conf file.

Run the container in Web server mode (and MCP server):

docker run -d --restart="always" -p 61208-61209:61208-61209 -e TZ="${TZ}" -e GLANCES_OPT="-w --enable-mcp" -v /var/run/docker.sock:/var/run/docker.sock:ro -v /run/user/1000/podman/podman.sock:/run/user/1000/podman/podman.sock:ro --pid host nicolargo/glances:latest-full

For a full list of options, see the Glances Docker documentation page.

It is also possible to use a simple Docker compose file to:

• run the Web (Rest API and WebUI) and the MCP server (see in ./docker-compose/docker-compose.yml):

mkdir -p ~/glances-compose
cd ~/glances-compose
wget https://raw.githubusercontent.com/nicolargo/glances/refs/heads/develop/docker-compose/docker-compose.yml
wget https://raw.githubusercontent.com/nicolargo/glances/refs/heads/develop/docker-compose/glances.conf
docker compose up

• or run the terminal client (TUI):

mkdir -p ~/glances-compose
cd ~/glances-compose
wget https://raw.githubusercontent.com/nicolargo/glances/refs/heads/develop/docker-compose/docker-compose-tui.yml
wget https://raw.githubusercontent.com/nicolargo/glances/refs/heads/develop/docker-compose/glances.conf
docker compose -f ./docker-compose-tui.yml run glances

For Linux and macOS, it is also possible to install Glances with Brew:

brew install glances

Glances is available on many Linux distributions, so you should be able to install it using your favorite package manager. Nevetheless, i do not recommend it. Be aware that when you use this method the operating system package for Glances may not be the latest version and only basics plugins are enabled.

Note: The Debian package (and all other Debian-based distributions) do not include anymore the JS statics files used by the Web interface (see issue 2021). If you want to add it to your Glances installation, follow the instructions here:. In Glances version 4 and higher, the path to the statics file is configurable (see issue 2621).

On FreeBSD, package name depends on the Python version.

Check for Python version:

# python --version

Install the Glances package:

# pkg install pyXY-glances

Where X and Y are the Major and Minor Values of your Python System.

# Example for Python 3.11.3: pkg install py311-glances

NOTE: Check Glances Binary Package Version for your System Architecture. You must have the Correct Python Version Installed which corresponds to the Glances Binary Package.

To install Glances from Ports:

# cd /usr/ports/sysutils/py-glances/
# make install clean

macOS users can install Glances using Homebrew or MacPorts.

$ brew install glances

$ sudo port install glances

Install Python for Windows (Python 3.4+ ship with pip) and follow the Glances Pip install procedure.

You need a rooted device and the Termux application (available on the Google Play Store).

Start Termux on your device and enter:

$ apt update
$ apt upgrade
$ apt install clang python
$ pip install fastapi uvicorn jinja2
$ pip install glances

And start Glances:

$ glances

You can also run Glances in server mode (-s or -w) in order to remotely monitor your Android device.

To install Glances from source:

$ pip install https://github.com/nicolargo/glances/archive/vX.Y.tar.gz

Note: Python headers are required to install psutil.

Glances includes shell tab autocompletion thanks to the --print-completion option.

For example, on a Linux operating system with bash shell:

$ mkdir -p ${XDG_DATA_HOME:="$HOME/.local/share"}/bash-completion
$ glances --print-completion bash > ${XDG_DATA_HOME:="$HOME/.local/share"}/bash-completion/glances
$ source ${XDG_DATA_HOME:="$HOME/.local/share"}/bash-completion/glances

Following shells are supported: bash, zsh and tcsh.

Glances is developed in Python. A minimal Python version 3.10 or higher should be installed on your system.

Note for Python 2 users

Glances version 4 or higher do not support Python 2 (and Python 3 < 3.10). Please uses Glances version 3.4.x if you need Python 2 support.

Dependencies:

• psutil (better with latest version)
• defusedxml (in order to monkey patch xmlrpc)
• packaging (for the version comparison)
• windows-curses (Windows Curses implementation) [Windows-only]
• shtab (Shell autocompletion) [All but Windows]
• jinja2 (for fetch mode and templating)

Extra dependencies:

• batinfo (for battery monitoring)
• bernhard (for the Riemann export module)
• cassandra-driver (for the Cassandra export module)
• clickhouse-connect (for the ClickHouse export module)
• chevron (for the action script feature)
• docker (for the Containers Docker monitoring support)
• elasticsearch (for the Elastic Search export module)
• FastAPI and Uvicorn (for Web server mode)
• mcp (for the MCP server — AI assistant integration)
• graphitesender (For the Graphite export module)
• hddtemp (for HDD temperature monitoring support) [Linux-only]
• influxdb (for the InfluxDB version 1 export module)
• influxdb-client (for the InfluxDB version 2 export module)
• kafka-python (for the Kafka export module)
• nats-py (for the NATS export module)
• nvidia-ml-py (for the GPU plugin)
• pycouchdb (for the CouchDB export module)
• pika (for the RabbitMQ/ActiveMQ export module)
• podman (for the Containers Podman monitoring support)
• potsdb (for the OpenTSDB export module)
• prometheus_client (for the Prometheus export module)
• pylxd (for the LXC Containers monitoring support)
• psycopg[binary] (for the PostgreSQL/TimeScale export module)
• pygal (for the graph export module)
• pymdstat (for RAID support) [Linux-only]
• pymongo (for the MongoDB export module)
• pysnmp-lextudio (for SNMP support)
• pySMART.smartx (for HDD Smart support) [Linux-only]
• pyzmq (for the ZeroMQ export module)
• requests (for the Ports, Cloud plugins and RESTful export module)
• sparklines (for the Quick Plugin sparklines option)
• statsd (for the StatsD export module)
• wifi (for the wifi plugin) [Linux-only]
• zeroconf (for the autodiscover mode)

If you want to contribute to the Glances project, read this wiki page.

There is also a chat dedicated to the Glances developers:

You can help me to achieve my goals of improving this open-source project or just say "thank you" by:

• sponsor me using one-time or monthly tier Github sponsors page
• send me some pieces of bitcoin: 185KN9FCix3svJYp7JQM7hRMfSKyeaJR4X

Any and all contributions are greatly appreciated.

Glances has been created by Nicolas Hennion (@nicolargo) <nicolas@nicolargo.com>

and developed by a wonderfull contributors community.

Glances is distributed under the LGPL version 3 license. See COPYING for more details.

Please give us a star on GitHub if you like this project.