About agentic-slackbot
agentic-slackbot is a Slack bot that uses the OpenAI Agents SDK to interact with an MCP server. It is intended for Slack users who want an agent-based bot, and can be run directly or in Docker.
Key features
- 01Slack bot interface
- 02OpenAI Agents SDK integration
- 03Environment-based configuration
- 04Docker execution
Use cases
- 01Interacting with an MCP server from Slack
- 02Running the bot in a Docker container
MCP support
The bot uses the OpenAI Agents SDK to interact with an MCP server; the README does not specify which MCP capabilities it exposes.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEagentic-slackbot
A simple Slack bot that uses the OpenAI Agents SDK to interact with the Model Context Protocol (MCP) server.
Install Dependencies
uv sync
Environment Variables
Create a .envrc file in the root directory of the project and add the following environment variables:
export OPENAI_API_KEY=""
export SLACK_BOT_TOKEN=""
export SLACK_APP_TOKEN=""
export OPENAI_MODEL="gpt-4o"
export HTTP_PROXY=""
If you are using Azure OpenAI, you can set the following environment variables instead:
AZURE_OPENAI_API_KEY=""
AZURE_OPENAI_ENDPOINT="https://<myopenai>.azure.com/"
OPENAI_MODEL="gpt-4o"
OPENAI_API_VERSION="2024-12-01-preview"
Running the Bot
uv run bot
Running the bot in docker
docker build . -t telegram-bot
docker run -e SLACK_BOT_TOKEN="" \
-e SLACK_APP_TOKEN="" \
-e HTTP_PROXY="" \
-e OPENAI_PROXY_BASE_URL="" \
-e OPENAI_PROXY_API_KEY="" \
-e OPENAI_MODEL=gpt-4o \
-e FIRECRAWL_API_URL="" telegram-bot
Credit
This project is based on the sooperset/mcp-client-slackbot example.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.