Teams Messenger MCP App

This project implements a pure Model Context Protocol (MCP) server that bridges Microsoft Teams and MCP-compatible clients (LLMs, agentic frameworks, and a rich CLI MCP client). All features are exposed via MCP tools, resources, and events—no REST API endpoints.

Features

• Microsoft Teams chat/message integration via MCP
• PostgreSQL-based Information Retrieval (IR) server for advanced search capabilities
• Persistent storage in DuckDB for chat/message history
• Hybrid semantic and lexical search (BM25 + vector, FlockMTL-style)
• CLI for login/token management and a rich MCP client for local testing
• Polling-based event emission for new messages
• Live event streaming and search for LLMs and CLI
• Single-agent (bot) account, not multi-user

Architecture

+-------------------+      +-------------------+      +-------------------+
|   CLI MCP Client  ||    MCP Server     ||  Microsoft Teams  |
| (rich terminal UI)|      | (Python, FastMCP) |      |  (Graph API)      |
+-------------------+      +-------------------+      +-------------------+
         |                        |                          
         |                        v                          
         |                +-------------------+      +-------------------+
         |                |     DuckDB DB     |      |    IR Server      |
         |                +-------------------+      | (PostgreSQL, API) |
                                                     +-------------------+
                                                              |
                                                              v
                                                     +-------------------+
                                                     |  PostgreSQL DB    |
                                                     |  (with pgvector)  |
                                                     +-------------------+

• All chat/message/search logic is via MCP tools/resources/events
• Teams MCP server uses DuckDB for message storage
• IR server provides advanced search capabilities with PostgreSQL and pgvector
• IR server exposes an HTTP API for MCP server communication

Installation

Requirements

• Python 3.9+
• pip
• Docker and Docker Compose (for containerized deployment)

Option 1: Local Installation

1. Clone the repository

git clone 
cd mcp-teams

2. Install dependencies

pip install -r requirements.txt

3. Configure environment variables

Copy the template and fill in your Azure AD/Teams credentials:

cp .env.template .env
# Edit .env and fill in your Azure AD and other settings

See the table below for variable descriptions.

Option 2: Docker Deployment (Recommended)

1. Clone the repository

git clone 
cd mcp-teams

2. Configure environment variables

Copy the template and fill in your credentials:

cp .env.template .env
# Edit .env and fill in your settings

3. Build and start services

docker-compose up -d

Environment Variables (.env)

Running the MCP Server

Local Mode (without Docker)

python mcp_server/server.py

Docker Mode (All Services)

docker-compose up -d

To check logs:

docker-compose logs -f teams_mcp  # Teams MCP server logs
docker-compose logs -f ir_server  # IR server logs

Demo Mode (no real Teams API calls)

Set DEMO_MODE=true in your .env and run as above.

CLI Usage

1. Login and Token Management

python cli/login.py login
python cli/login.py status
python cli/login.py logout

2. Rich CLI MCP Client

All commands below use the MCP stdio protocol to talk to the server.

List chats

python cli/mcp_client.py list_chats

Get messages from a chat

python cli/mcp_client.py get_messages 

Send a message

python cli/mcp_client.py send_message  "Hello from CLI!"

Create a new 1:1 chat

python cli/mcp_client.py create_chat 

Search messages (hybrid, BM25, or vector)

python cli/mcp_client.py search_messages "project update" --mode hybrid --top_k 5

Stream new incoming messages (live event subscription)

python cli/mcp_client.py stream

IR Server Usage

The IR server provides advanced search capabilities with PostgreSQL and pgvector. It exposes an HTTP API for MCP server communication.

IR Server API Endpoints

1. Health Check

GET http://localhost:8090/

2. List Available Tools

GET http://localhost:8090/api/tools

3. Search Content

POST http://localhost:8090/api/tools/search

Body:

{
  "query": "your search query",
  "search_type": "hybrid",
  "limit": 10
}

4. Index Content

POST http://localhost:8090/api/tools/index_content

Body:

{
  "content": "Text content to index",
  "source_type": "teams",
  "metadata": {
    "author": "User Name",
    "created": "2025-04-01T12:00:00Z"
  }
}

For more detailed IR server documentation, see ir/README.md.

Search and Event Streaming

• Hybrid search: Combines BM25 and vector search with LLM reranking
• Live streaming: Subscribe to messages/incoming for real-time updates

Development & Extension

• Add new MCP tools/resources in mcp_server/server.py
• Extend Teams integration in teams/graph.py
• Modify IR capabilities in the IR server
• Add analytics, summarization, or RAG features using DuckDB, PostgreSQL, and LLMs
• Use the CLI as a test harness for all MCP features

Troubleshooting & FAQ

• Login fails: Check your Azure AD credentials and .env values
• No messages appear: Ensure polling is running and your bot account is in the Teams chat
• DuckDB errors: Check file permissions and paths in .env
• IR server not responding: Check Docker logs and ensure the container is running
• Demo mode: Set DEMO_MODE=true for local testing without real Teams

References

• Beyond Quacking: Deep Integration of Language Models and RAG into DuckDB (FlockMTL)
• Model Context Protocol documentation
• Microsoft Graph API docs
• PostgreSQL with pgvector extension

For full product details, see specs/app-spec.md.

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