Tiger Slack
Integrates Slack data in real-time to power agentic AI assistants with conversational memory.
About
Tiger Slack empowers AI assistants to understand and naturally engage with team conversations by providing real-time access to message history and context. Through a specialized Model Context Protocol (MCP) server, it enables AI bots to respond to questions with the same contextual awareness as humans, understanding references to past discussions, ongoing projects, and team dynamics. This platform allows AI assistants to participate meaningfully in team conversations, answer questions about project history and decisions, know who's involved in different topics, and follow ongoing discussions to provide relevant input.
Key Features
- Real-time Slack message and event ingestion via WebSocket
- TimescaleDB integration for high-throughput, time-series data storage and full-text search
- Model Context Protocol (MCP) server providing AI-accessible APIs for Slack data analysis
- Contextual understanding of past discussions, ongoing projects, and team dynamics
- Comprehensive observability with Logfire integration for monitoring and debugging
- 2 GitHub stars
Use Cases
- Enabling AI bots to answer questions about project history and past decisions within Slack.
- Allowing AI assistants to understand conversational context and references to previous discussions.
- Providing AI bots with knowledge of who's involved in different topics and threads for informed responses.
Sponsored