Model Context Protocol (MCP) 서버와 연결되는 Mattermost 통합은 LangGraph 기반 AI 에이전트를 활용하여 사용자가 상호 작용하고 Mattermost 내에서 도구를 직접 실행하는 지능형 인터페이스를 제공합니다.

데모

##1. Github Agent in support channel - 기존 문제와 PR을 검색하고 찾을 수없는 경우 새로운 문제를 만듭니다.

##2. 인터넷 검색 및 Mattermost-MCP-server를 사용하여 채널에 게시

YouTube에서 전체 데모를 위해 아래 스크롤

특징

• LOG **Langgraph Agent 통합 **: 사용자 요청과 관현악을 이해하기 위해 LangGraph 에이전트를 사용합니다.
• Azur MCP Server Integration: mcp-servers.json]에 정의된 여러 MCP 서버에 연결한다.
• 542️ Dynamic Tool Load: 자동적으로 연결된 MCP 서버에서 도구를 발견하고 AI 에이전트에 사용할 수 있습니다. MCP 도구를 langchain 구조 도구로 변환합니다.
• ✅ Thread-Aware Conversations: 무장한 상호 작용을 위한 Mattermost 스레드 내에서 대화식 컨텍스트를 유지합니다.
• ܧIntelligent Tool Use: AI Agent는 사용자 요청을 충족하기 위해 사용할 수 있는 도구를 사용할 때 결정할 수 있습니다.

Mattermost MCP Host

A Mattermost integration that connects to Model Context Protocol (MCP) servers, leveraging a LangGraph-based AI agent to provide an intelligent interface for interacting with users and executing tools directly within Mattermost.

Demo

1. Github Agent in support channel - searches the existing issues and PRs and creates a new issue if not found

2. Search internet and post to a channel using Mattermost-MCP-server

Scroll below for full demo in YouTube

Features

• 🤖 Langgraph Agent Integration: Uses a LangGraph agent to understand user requests and orchestrate responses.
• 🔌 MCP Server Integration: Connects to multiple MCP servers defined in mcp-servers.json.
• 🛠️ Dynamic Tool Loading: Automatically discovers tools from connected MCP servers and makes them available to the AI agent. Converts MCP tools to langchain structured tools.
• 💬 Thread-Aware Conversations: Maintains conversational context within Mattermost threads for coherent interactions.
• 🔄 Intelligent Tool Use: The AI agent can decide when to use available tools (including chaining multiple calls) to fulfill user requests.
• 🔍 MCP Capability Discovery: Allows users to list available servers, tools, resources, and prompts via direct commands.
• #️⃣ Direct Command Interface: Interact directly with MCP servers using a command prefix (default: #).

Overview

The integration works as follows:

1. Mattermost Connection (mattermost_client.py): Connects to the Mattermost server via API and WebSocket to listen for messages in a specified channel.
2. MCP Connections (mcp_client.py): Establishes connections (primarily stdio) to each MCP server defined in src/mattermost_mcp_host/mcp-servers.json. It discovers available tools on each server.
3. Agent Initialization (agent/llm_agent.py): A LangGraphAgent is created, configured with the chosen LLM provider and the dynamically loaded tools from all connected MCP servers.
4. Message Handling (main.py):
   • If a message starts with the command prefix (#), it’s parsed as a direct command to list servers/tools or call a specific tool via the corresponding MCPClient.
   • Otherwise, the message (along with thread history) is passed to the LangGraphAgent.
5. Agent Execution: The agent processes the request, potentially calling one or more MCP tools via the MCPClient instances, and generates a response.
6. Response Delivery: The final response from the agent or command execution is posted back to the appropriate Mattermost channel/thread.

Setup