Slackbot MCP

by adamkleingit

316 downloads
Not rated
GitHub

About

A Slackbot LLM agent that allows connecting to an LLM and MCP servers

Details

Author
adamkleingit
Downloads
316
Categories
AI

- Slack integration via Events API
- LLM-powered responses
- MCP tool integration
- Multi-bot management
- Thread-aware conversations
- Channel-specific configurations

To set up, clone the repository, install dependencies with Poetry, copy the .env.example file, start Docker Compose (PostgreSQL, Redis), run Alembic migrations, and start the Uvicorn server. Detailed steps are provided in the README.

Slackbot MCP

A powerful Slack bot powered by LLM with MCP integration capabilities.

Features

- Slack integration with Events API
- LLM-powered responses
- MCP tool integration
- Multi-bot management
- Thread-aware conversations
- Channel-specific configurations

Prerequisites

- Python 3.9+
- Poetry for dependency management
- Docker and Docker Compose
- PostgreSQL
- Redis

Development Setup

1. Clone the repository:

git clone <repository-url>
cd slackbot-mcp

2. Install dependencies:

poetry install

3. Set up pre-commit hooks:

poetry run pre-commit install

4. Copy the example environment file:

cp .env.example .env

5. Start the development environment:

docker-compose up -d

6. Run migrations:

poetry run alembic upgrade head

7. Start the development server:

poetry run uvicorn src.slackbot.api.main:app --reload

Project Structure

slackbot-mcp/
├── src/
│   └── slackbot/
│       ├── api/        # FastAPI application and endpoints
│       ├── core/       # Core business logic
│       ├── models/     # SQLAlchemy models
│       ├── services/   # External service integrations
│       └── utils/      # Utility functions
├── tests/
│   ├── unit/          # Unit tests
│   └── integration/   # Integration tests
├── scripts/           # Utility scripts
├── alembic/           # Database migrations
└── docker/           # Docker configuration files

Contributing

1. Create a new branch for your feature
2. Make your changes
3. Run tests: poetry run pytest
4. Submit a pull request

License

[Your chosen license]

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