What is Slack Search

Slack-Search is a local AI-powered search interface designed to enhance the experience of searching through Slack export logs using the Model Context Protocol (MCP) and Claude Desktop.

Use cases

Use cases for Slack-Search include retrieving historical discussions, finding specific topics or keywords in Slack channels, and enhancing team productivity by quickly accessing relevant information from Slack logs.

How to use

To use Slack-Search, clone the repository, set up a virtual environment, install the required dependencies, and configure Claude Desktop to connect to the MCP server. Once set up, you can query Slack data using natural language directly in Claude Desktop.

Key features

Key features of Slack-Search include local and private searching of Slack logs, integration with Claude Desktop for natural language queries, and the ability to parse and register custom MCP resources for intelligent search.

Where to use

Slack-Search can be used in various fields such as team collaboration, project management, and any environment where Slack is utilized for communication and documentation.

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

A local, AI-powered Slack search interface that uses Model Context Protocol (MCP) to enhance Claude Desktop experience. This project helps you search and retrieve meaningful insights from Slack export logs, all locally and privately.

What is This?

This project sets up a local MCP server (mcp_server.py) that parses Slack export logs and registers custom MCP resources for intelligent search. It integrates with Claude Desktop via a JSON config (claude_desktop_config.json), allowing you to query Slack data directly using natural language.

Project Structure

├── mcp_server.py               # The MCP server that registers search resources
├── claude_desktop_config.json # Config file for Claude Desktop to connect to this server
├── Slack-dataset/              # Slack dataset (not included)
└── README.md                   

Dataset found at: https://github.com/preethac/Software-related-Slack-Chats-with-Disentangled-Conversations

⚙️ Setup Instructions

1. Clone the repo

git clone https://github.com/AdilFayyaz/Slack-Search.git
cd Slack-Search

2. Set up a virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

3. Update Claude Desktop Config

Paste the following into your Claude Desktop config file:

{
  "mcpServers": {
    "search_slack": {
      "command": "/bin/zsh",
      "args": [
        "-c",
        "source /Users/yourname/path-to-project/.venv/bin/activate && python3 /Users/yourname/path-to-project/mcp_server.py"
      ],
      "host": "127.0.0.1",
      "port": 5000,
      "timeout": 10000
    }
  }
}

Make sure to update file paths to your local machine setup.

Usage

Open Claude Desktop, and try queries like:

Search for onboarding discussions from February.
What did we say about the pricing model in #general?
Find mentions of "launch" in random.

Claude will use search:// and summary:// style MCP URIs behind the scenes to get you results from your local server.

How it Works

• The MCP server parses Slack JSON files and indexes content.
• It registers searchable resources like search://{query} or summary://{channel}.
• Claude Desktop makes MCP calls to your server to fetch and return contextual results.

Motivation

Slack is where decisions happen and get buried. This tool helps resurface important context from old threads without uploading your data to the cloud. It’s a small step toward smarter, local-first search powered by AI.

Acknowledgments

• Claude Desktop
• Model Context Protocol (MCP)