Give agents tools for secure, real-time access to fetch, search, write, and sync across every system, with replication, entity mapping, and auth built-in.
About this Connector
Slack is a business communication platform that offers messaging, file sharing, and integrations with other tools. This connector provides read access to users, channels, channel members, channel messages, and threads, plus write operations including sending messages, creating channels, and adding reactions.
CRM
Sales Analytics
Customer Data
Version Information
Package version
0.1.70
Connector version
0.1.15
SDK commit
cb4380e76ac5cbc67b9089f94522be1bbe9f8d73
Support Open Source
Check us out on Github and join the Airbyte community
Installation & Usage
1
Install Package
Using uv or pip
bash
uv pip install airbyte-agent-slack
2
Import
Initialize and use
python
from airbyte_agent_slack import SlackConnector
from airbyte_agent_slack.models import SlackTokenAuthenticationAuthConfig
connector = SlackConnector(
auth_config=SlackTokenAuthenticationAuthConfig(
api_token="<Your Slack Bot Token (xoxb-) or User Token (xoxp-)>"
)
)3
Tool
Add tools to your agent
python
@agent.tool_plain # assumes you're using Pydantic AI
@SlackConnector.tool_utils
async def slack_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})Supported Entities & Actions
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| Entity | Actions |\n|--------|---------|\n| Users | [List](./REFERENCE.md#users-list), [Get](./REFERENCE.md#users-get), [Search](./REFERENCE.md#users-search) |\n| Channels | [List](./REFERENCE.md#channels-list), [Get](./REFERENCE.md#channels-get), [Create](./REFERENCE.md#channels-create), [Update](./REFERENCE.md#channels-update), [Search](./REFERENCE.md#channels-search) |\n| Channel Messages | [List](./REFERENCE.md#channel-messages-list) |\n| Threads | [List](./REFERENCE.md#threads-list) |\n| Messages | [Create](./REFERENCE.md#messages-create), [Update](./REFERENCE.md#messages-update) |\n| Channel Topics | [Create](./REFERENCE.md#channel-topics-create) |\n| Channel Purposes | [Create](./REFERENCE.md#channel-purposes-create) |\n| Reactions | [Create](./REFERENCE.md#reactions-create) |
Example Prompts
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List all users in my Slack workspace - Show me all public channels - List members of a public channel - Show me recent messages in a public channel - Show me thread replies for a recent message - List all channels I have access to - Show me user details for a workspace member - List channel members for a public channel - Send a message to a channel saying 'Hello team!' - Post a message in the general channel - Update the most recent message in a channel - Create a new public channel called 'project-updates' - Create a private channel named 'team-internal' - Rename a channel to 'new-channel-name' - Set the topic for a channel to 'Daily standup notes' - Update the purpose of a channel - Add a thumbsup reaction to the latest message in a channel - React with :rocket: to the latest message in a channel - Reply to a recent thread with 'Thanks for the update!' - What messages were posted in channel \{channel_id\} last week? - Show me the conversation history for channel \{channel_id\} - Search for messages mentioning \{keyword\} in channel \{channel_id\}
Why Airbyte for AI Agents?
Built for production AI workloads with enterprise-grade reliability
Agent-Native Design
Structured, LLM-friendly schemas optimized for AI agent consumption with natural language query support.
Secure Authentication
Built-in OAuth 2.0 handling with automatic token refresh. No hard-coded credentials.
Production Ready
Battle-tested connectors with comprehensive error handling, logging, and retry logic.
Open Source
Fully open source under the MIT license. Contribute, customize, and extend freely.
Works with your favorite frameworks
🦜
LangChain
🦙
LlamaIndex
🤖
CrewAI
⚡
AutoGen
🧠
OpenAI Agents SDK
🔮
Claude Agents SDK
Frequently Asked Questions
Didn't find your answer? Please don't hesitate to reach out.
The Slack connector supports token-based authentication using either a Slack Bot Token (xoxb-) or a User Token (xoxp-). In hosted mode, credentials are stored securely in Airbyte Cloud and you authenticate using your Airbyte client ID and client secret instead.
Can I use this connector with any AI agent framework?
The connector is compatible with any Python-based AI agent framework including LangChain, LlamaIndex, CrewAI, Pydantic AI, and custom implementations.
Does this connector support write operations?
Yes, the Slack connector supports write operations including sending and updating messages, creating and renaming channels, setting channel topics and purposes, and adding reactions to messages. Operations not currently supported include deleting messages, removing reactions, archiving channels, inviting or removing users, and managing user profiles.
How is this different from the Airbyte data connector?
Agent connectors are specifically designed for AI agents and LLM applications. They provide natural language interfaces, optimized response formats, and seamless integration with agent frameworks, unlike traditional ETL-focused connectors.
Will there be a platform for agent connectors?
The hosted version with secure credential storage through Airbyte Cloud is already available. See the hosted usage section in the documentation for setup instructions.