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mattermost/mattermost

📈 Trending36,748TypeScriptAudience · ops devopsComplexity · 4/5ActiveLicenseSetup · hard

TLDR

Self-hosted team chat platform like Slack or Teams that runs entirely on your own servers, giving you full control over your data and conversations.

Mindmap

mindmap
  root((Mattermost))
    What it does
      Team channels
      Direct messages
      File sharing
      Voice calling
    Features
      700+ integrations
      Webhook and bot API
      AI integrations
      Search
    Deployment
      Single binary
      Docker support
      Kubernetes ready
      PostgreSQL database
    Tech stack
      Go backend
      React frontend
      TypeScript
      PostgreSQL
    Use cases
      Sensitive data orgs
      Custom workflows
      Compliance needs
      On-premise only

Things people build with this

USE CASE 1

Deploy a private messaging platform for government, healthcare, or finance teams that cannot use cloud-based Slack or Teams.

USE CASE 2

Build custom chat workflows and automations using webhooks and bots without relying on third-party SaaS integrations.

USE CASE 3

Run a fully on-premise collaboration tool that meets strict data residency and compliance requirements.

USE CASE 4

Integrate voice calling and screen sharing into your organization's internal communication without external dependencies.

Tech stack

GoTypeScriptReactPostgreSQLDockerKubernetes

Getting it running

Difficulty · hard Time to first run · 1day+

Requires PostgreSQL database, Docker/Kubernetes orchestration, and multiple service components to coordinate.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice and license text.

In plain English

Mattermost is an open-source, self-hosted team collaboration platform, essentially an alternative to Slack or Microsoft Teams that organizations can run entirely on their own infrastructure. The core problem it solves is the tension between modern team communication tools (real-time chat, file sharing, workflow automation) and enterprise requirements for data control, security, and compliance. Commercial SaaS messaging platforms store all your conversations on their servers; Mattermost lets you keep everything inside your own network. The platform provides persistent team channels, direct messages, threaded conversations, voice calling, screen sharing, file sharing, and search. It has an app marketplace with over 700 integrations, a webhook and bot API for automation, and built-in support for AI integrations. The web interface is built in React, and native clients exist for iOS, Android, Windows, macOS, and Linux. The server is written in Go and ships as a single Linux binary, which makes deployment straightforward: you run the binary, point it at a PostgreSQL database, and it is running. Docker, Kubernetes, Helm, and various Linux package install paths are all supported. The codebase is a monorepo that includes both the server and the web client. New releases follow a monthly schedule, releasing on the 16th under an MIT license for the core platform. You would deploy Mattermost if your organization handles sensitive information (government, healthcare, finance, defense) and cannot use cloud SaaS messaging, or if you need deep customization, custom workflows, compliance integrations, or specialized automations, that commercial tools don't support. The tech stack is Go for the backend server, TypeScript and React for the web client, and PostgreSQL for the database.

Copy-paste prompts

Prompt 1
How do I deploy Mattermost on Kubernetes with PostgreSQL and enable SSL certificates for production?
Prompt 2
Show me how to create a custom bot using Mattermost's webhook API that posts daily standup reminders to a channel.
Prompt 3
What are the steps to migrate our team from Slack to a self-hosted Mattermost instance, including user data and message history?
Prompt 4
How do I configure Mattermost to integrate with our existing LDAP directory for single sign-on authentication?
Prompt 5
What's the process to add custom AI integrations to Mattermost for automated message summarization or sentiment analysis?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.