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Mattermost

by mattermostversion 2.12.0i★ –iRuns in the cloud
Registry nameio.github.mattermost/mattermost-plugin-agents

Install

Overview

Description from the maker (original English)

Official Mattermost MCP server, built into the Mattermost Agents plugin. Read, search and post.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs in the cloud
  • Transport: Streamable HTTP
  • Category: Search & AI memory
  • You need to fill in: Authorization

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on the maker’s server: what you ask it goes through their server.
  • You fill in yourself: Authorization

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Run this in your terminal

claude mcp add --transport http mattermost-plugin-agents 'https://{mattermost_host}/plugins/mattermost-ai/mcp-server/mcp' --header 'Authorization: Bearer {personal_access_token}'

Fill in the empty values before running it.

The address contains {…} parts that only you know (such as your account), so copy it and fill them in.

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "mattermost-plugin-agents": {
      "url": "https://{mattermost_host}/plugins/mattermost-ai/mcp-server/mcp",
      "headers": {
        "Authorization": "Bearer {personal_access_token}"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

The address contains {…} parts that only you know (such as your account), so copy it and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "mattermost-plugin-agents": {
      "type": "http",
      "url": "https://{mattermost_host}/plugins/mattermost-ai/mcp-server/mcp",
      "headers": {
        "Authorization": "Bearer {personal_access_token}"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • Authorization secret HTTP header
    Optional. OAuth 2.0 with dynamic client registration is the default and needs no header. To use a Mattermost Personal Access Token instead, set this to Bearer followed by the token.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

The address needs your own values, so we cannot read the tool list for you.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account mattermost, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    The address needs your own account values, so we cannot check it for you

  • – Not applicable

    Sign-in with OAuth

    The address needs your own account values, so we cannot check it for you

  • … Not checked yet

    No hidden instructions in tool descriptions

    Not checked yet; we read the tool list when we check the endpoint

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7231 servers in this category
  • Published to the registry more recently than 93% of the other 7231 servers in this category
  • Basic checks equal to or better than 100% of the other 7231 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Mattermost safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: Authorization

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.12.0) reached the registry 3 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated 3 days ago
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 44 days ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Mattermost Agents Plugin

Self-hosted AI agents for Mattermost that act on your behalf through tools and MCP servers, plus a built-in Mattermost MCP server for external AI clients such as Claude Code, Claude Desktop, Cursor, and VS Code.

Mattermost Agents (plugin ID mattermost-ai) adds AI agents to a Mattermost server. You talk to an agent in a direct message, the Agents pane, or a channel. The agent can search and post in Mattermost, call tools on other systems through the Model Context Protocol (MCP), and work with files, all with the permissions of the person it is acting for. You choose the LLM, including models that run on your own infrastructure, so with a self-hosted model, conversations and data stay in your environment.

Does Mattermost have an official MCP server? Yes. It is built into this plugin and needs no separate installation. After an admin enables it, MCP clients connect to /plugins/mattermost-ai/mcp-server/mcp on your Mattermost server and sign in as a Mattermost user. See Mattermost MCP Server.

Key Features

  • Agents that act on your behalf: Chat with a personal agent that searches and reads Mattermost, posts and sends messages, schedules posts and reminders, and uses tools from other systems. Configure multiple agents with their own instructions, models, and tool access. See Use Mattermost Agents as your personal AI assistant.
  • Tools and MCP: Agents use built-in Mattermost tools, remote MCP servers with per-user OAuth (with a Connect card in the conversation), and tools registered by other Mattermost plugins. Dynamic tool loading keeps large tool catalogs out of the model's context.
  • Built-in Mattermost MCP server: Connect Claude Code, Claude Desktop, Cursor, VS Code, or any MCP client that supports streamable HTTP to Mattermost, using OAuth with dynamic client registration or a personal access token. Over 100 tools run with the signed-in user's own permissions. See Mattermost MCP Server.
  • Governance: Per-tool approval policies, user, team, and channel access controls for agents, attribute-based access control, server audit logging, token usage tracking, and OpenTelemetry tracing. Admins decide which tools exist and which need approval. See the Admin Guide.
  • Bring your own LLM: Use local models through OpenAI-compatible APIs (Ollama, vLLM), or OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Google Gemini and Vertex AI, Cohere, Mistral, and Scale AI. See LLM Provider Configuration and Implementing Sovereign AI.
  • Summaries, search, and meetings: Summarize threads, unread messages, and channels; ask questions about a channel; search with keyword and semantic search; and summarize Mattermost Calls and Zoom meeting recordings.
  • Files and artifacts: Agents create text files attached to their replies, read attachments, analyze images with vision-capable models, and render HTML artifacts in the conversation.
  • Channel use: @mention an agent in a channel, or set a channel to auto-reply. Tool results in channels can be shared or kept private by the person who asked.
  • Custom prompts: Save reusable prompts, pin them in the Agents pane, and share them with your team.

Some features depend on your Mattermost license level. See the license requirements.

Documentation

Documentation is available in the docs directory:

  • User Guide: Use agents, tools, summaries, search, and meeting summaries
  • Use Mattermost Agents as your personal AI assistant: What a personal agent can do across channels, MCP servers, and integrations
  • Admin Guide: Installation, configuration, MCP servers, tool policies, access control, audit logging, tracing, and license requirements
  • Mattermost MCP Server: Connect Claude Code, Claude Desktop, Cursor, VS Code, and other MCP clients to Mattermost
  • LLM Provider Configuration: Configuration for supported LLM providers
  • AWS Bedrock Setup: Use Amazon Bedrock with IAM instance profiles
  • Implementing Sovereign AI: Deploy agents with local models and data control
  • Usage Tips: Voice dictation, prompting techniques, and workflow tips
  • Upgrading to Agents V2: Upgrade path, automatic migrations, and breaking changes from v1.x
  • Load Testing: Configure the in-process mock LLM and load-test-ng Agents controller
  • Feature documentation:
  • Managing Agents: Create, edit, and version agents and control their access and MCP tools
  • Custom Prompts: Save, share, and pin reusable prompts
  • Channel Summaries: Use the Ask Agents about this channel button to summarize and analyze channel activity
  • Multiplayer Tool Calling: Tool approval, credentials, and result visibility in shared channels

Installation

  1. Download the latest release from the releases page. You can also download the experimental latest master
  2. Upload and enable the plugin through the Mattermost System Console
  3. Configure your desired LLM provider settings
System Requirements
  • Mattermost Server v12.0.0+
  • PostgreSQL database with pgvector extension for semantic search capabilities
  • Network access to your chosen LLM provider

Quick Start

After installation, complete these steps to get started:

  1. Navigate to System Console > Plugins > Agents
  2. Create an agent and configure it with your LLM provider credentials
  3. Set permissions for who can access the agent
  4. Open the Agents panel from any channel using the AI icon in the right sidebar
  5. Start interacting with your AI assistant

For detailed configuration instructions, see the Admin Guide.

Integration

Bridge Client

The plugin provides a Go client library for other Mattermost plugins and the Mattermost server to interact with the AI plugin's LLM Bridge API. This allows you to easily add AI capabilities to your own plugins or server-side features.

See the Bridge Client README for installation and usage instructions.

Development

Prerequisites
  • Go 1.27+
  • Node.js 24.11+
  • Access to an LLM provider (OpenAI, Anthropic, etc.)
Local Setup
  1. Setup your Mattermost development environment by following the Mattermost developer setup guide. If you have a remote mattermost server you want to develop to you can skip this step.
  1. Setup your Mattermost plugin development environment by following the Plugin Developer setup guide.
  1. Clone the repository:
git clone https://github.com/mattermost/mattermost-plugin-agents.git

cd mattermost-plugin-agents

  1. Optional. If you are developing to a remote server, setup environment variables to deploy:
MM_SERVICESETTINGS_SITEURL=http://localhost:8065

MM_ADMIN_USERNAME= MM_ADMIN_PASSWORD=

  1. Run deploy to build the plugin
make deploy
Other make commands
  • Run make help for a list of all make commands
  • Run make check-style to verify code style
  • Run make test to run the test suite
  • Run make e2e to run the e2e tests
  • Run make evals to run prompt evaluations interactively (with TUI)
  • Run make evals-ci to run prompt evaluations in CI mode (non-interactive)
Benchmark Tests

The streaming code has benchmark tests to measure performance and detect regressions:

# Run all streaming benchmarks

go test -bench=. -benchmem ./llm/... ./streaming/...

Run specific benchmark

go test -bench=BenchmarkStreamToPost -benchmem ./streaming/...

Run with CPU profiling

go test -bench=BenchmarkReadAll -cpuprofile=cpu.prof ./llm/...

Benchmarks cover:

  • ReadAll() stream consumption with varying response sizes
  • TokenUsageLoggingWrapper interception overhead
  • StreamToPost() full processing pipeline with WebSocket events
Multi-Provider Evaluation Support

The evaluation system supports testing with multiple LLM providers: OpenAI, Anthropic, and Azure OpenAI. By default, evaluations run against all providers, but you can target specific ones:

# Run with all providers (default)

make evals

Run with only Anthropic

LLM_PROVIDER=anthropic make evals

Run with OpenAI and Azure

LLM_PROVIDER=openai,azure make evals

Use a specific model

ANTHROPIC_MODEL=claude-opus-5-5 make evals

See cmd/evalviewer/README.md for complete documentation on environment variables and configuration options.

License

This repository is licensed under Apache-2, except for the enterprise directory which is licensed under the Mattermost Source Available License. See Mattermost Source Available License to learn more.

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