From Slack Logs to Smart Search — Powered by MCP and Claude Desktop

Name: From Slack Logs to Smart Search — Powered by MCP and Claude Desktop
Author: AdilFayyaz

@AdilFayyaz

About From Slack Logs to Smart Search — Powered by MCP and Claude Desktop

Using Model Context Protocol (MCP) to build a local Slack thread searcher with Claude Desktop and a lightweight Python server.

#slack #search #mcp #claude-desktop

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "Slack-Search": {
      "command": "python3",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is From Slack Logs to Smart Search — Powered by MCP and Claude Desktop?

A local MCP server that parses Slack export logs and registers custom MCP resources for intelligent search, integrating with Claude Desktop to allow natural language queries of Slack data privately and locally.

How to use From Slack Logs to Smart Search — Powered by MCP and Claude Desktop?

Clone the repository, set up a Python virtual environment, install dependencies, and update the Claude Desktop config file (claude_desktop_config.json) with the correct paths to the virtual environment and mcp_server.py. Then open Claude Desktop and ask queries like “Search for onboarding discussions from February” or “Find mentions of ‘launch’ in random.”

Key features of From Slack Logs to Smart Search — Powered by MCP and Claude Desktop

Local, private search of Slack export logs
AI-powered natural language querying via Claude Desktop
Registers MCP resources: search://{query} and summary://{channel}
No cloud upload – data stays on your machine
Simple setup with Python virtual environment and Claude Desktop config

Use cases of From Slack Logs to Smart Search — Powered by MCP and Claude Desktop

Search for specific discussions (e.g., “onboarding discussions from February”)
Query for decisions or mentions in a channel (e.g., “pricing model in #general”)
Find all mentions of a keyword across Slack exports (e.g., “launch” in random)
Resurface important context from old threads without leaving Claude Desktop

FAQ from From Slack Logs to Smart Search — Powered by MCP and Claude Desktop

What does this project do?

It sets up a local MCP server that parses Slack export logs and registers custom resources (search:// and summary://) so that Claude Desktop can search Slack data using natural language.

What data does it use?

The project expects a “Slack-dataset” folder containing Slack export JSON files. A sample dataset is available at https://github.com/preethac/Software-related-Slack-Chats-with-Disentangled-Conversations.

How does it integrate with Claude Desktop?

You add the MCP server configuration to Claude Desktop’s config file (claude_desktop_config.json), pointing to the local mcp_server.py script. Claude Desktop then makes MCP calls to fetch and return contextual results.

Is my data kept private?

Yes. The server runs entirely locally, and no data is uploaded to the cloud. The README emphasizes “all locally and privately” and “without uploading your data to the cloud.”

What are the runtime requirements?

Python 3, a virtual environment, and the requirements.txt packages. The server is started via a command in the Claude Desktop config (e.g., using /bin/zsh to activate the venv and run mcp_server.py).