MCPSERV.CLUB
AdilFayyaz

Slack Search MCP Server

MCP Server

Local AI-powered Slack search without cloud upload

Stale(50)
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Updated May 8, 2025

About

A local Model Context Protocol server that parses exported Slack logs and exposes intelligent search and summary endpoints for Claude Desktop, enabling private, natural‑language queries over your Slack data.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

The Slack Search MCP server turns a static export of Slack conversations into an AI‑powered, privacy‑first search engine that plugs directly into Claude Desktop. By exposing the data through Model Context Protocol (MCP) resources, it lets developers query Slack history with natural language while keeping all the data on their own machine. This eliminates the need to upload sensitive chat logs to external services, a critical concern for teams that handle confidential discussions or regulatory‑compliant information.

The server parses the JSON export from Slack and builds an internal index of messages, channels, and user metadata. It then registers two primary MCP resources:

  • – returns the most relevant messages that match a free‑text query.
  • – provides a concise overview of the content within a specified channel.

When Claude Desktop sends an MCP request, the server processes it on‑the‑fly and streams back a formatted response that Claude can embed in its replies. This tight integration means users can ask questions like “What did we say about the pricing model in #general?” or “Find mentions of ‘launch’ in random.” and receive instant, context‑rich answers without leaving the chat interface.

For developers building AI workflows that rely on historical Slack data, this MCP server offers several tangible advantages. It preserves data sovereignty by keeping everything local, reduces latency compared to cloud‑based search services, and leverages Claude’s language understanding to surface insights that would otherwise require manual scrolling. The server also supports custom prompts and sampling options, allowing teams to fine‑tune how summaries are generated or how search relevance is weighted.

Real‑world scenarios include onboarding new hires, where a recruiter can quickly retrieve past discussions about training programs; product teams looking to audit decision logs for feature rollouts; or compliance officers auditing conversations for policy adherence. By turning raw Slack exports into an AI‑enabled knowledge base, the Slack Search MCP server empowers organizations to harness their own data safely and efficiently.