tiger-slack
Active·★ 49·Apache-2.0·Updated 2026-10-20
Tiger Slack enhances AI Slack bots with conversational memory by providing real-time access to Slack message history and context. This enables AI assistants to understand and engage with team discussions naturally, responding to questions with human-like contextual awareness.
#AI Bots#Slack Integration#Conversational Memory#TimescaleDB#Contextual AI#Real-time Data#MCP Server#LLM Integration
01
Features
01Understand conversational context and past discussions.
02Answer questions about project history and decisions.
03Build conversational memory across all team channels.
04Real-time Slack message and event ingestion.
05Provide AI-accessible APIs for Slack data analysis.
02
Compatibility
Python
Runtime
Verified via docs
TypeScript
Runtime
Verified via docs
TimescaleDB
Database
Verified via docs
Docker
Containerization
Verified via docs
Slack
Integration Platform
Verified via docs
03
Quick start
1
$ git clone --recurse-submodules [email protected]:timescale/tiger-slack.git
2
$ cd tiger-slack
3
$ cp .env.sample .env
4
$ ./setup-tiger-slack.sh
5
$ docker compose up -d --build
04
Use cases
↳Improve AI bot responses by leveraging full conversational history.
↳Enable AI assistants to answer questions about project history and decisions.
↳Transform Slack workspaces into intelligent knowledge bases for AI analytics.
↳Monitor and understand team dynamics and participant involvement in discussions.
05
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