TwinsSlack
A Slack twin for testing AI agents.
Test agents that answer questions, coordinate people and act across channels and threads, with nothing reaching a real workspace.
A stateful copy of Slack, built for testing agents.
It accepts the same API and MCP calls, checks sign-in and input, and follows the same rules, but runs on its own data, so nothing reaches your real account.
- Messages, threads and replies
- Channels, DMs and membership
- Reactions, mentions and files
- Search
- App permissions and rate limits
Every run starts from a company that already has history. We seed:
- A workspace with public and private channels
- DMs and threads with real history
- Users, groups and statuses
- Files and pinned messages
Use Slack in staging, without using production.
Validate every action
The twin checks what the agent sends the way Slack would: required fields, permissions, rate limits, malformed input. Mistakes fail here, not in your account.
Start from a realistic state
Describe the company and the situation in plain English. Drizz seeds the twin to match, and resets it to that state before every run.
Replay tasks across tools
The Slack twin shares its people, customers and history with the other twins, so a task that touches three tools runs the way it would at work.
Swap the address. Your agent code stays the same.
Replace the live Slack endpoint with the twin’s. Everything your agent already does keeps working, on data that is yours to break.
{
"mcpServers": {
"slack": {
"type": "http",
"url": "<twin MCP endpoint>",
"headers": { "Authorization": "Bearer <token>" }
}
}
}REST works on the same data. Both are reset with one call.
Connected to the rest of the company.
The people in Slack are the same people in Gmail and Jira. A channel about a customer carries the same deal, tickets and meetings the other twins hold.
Read the guide: How to test AI agents before production →