From Slack Logs to Smart Search — Powered by MCP and Claude Desktop
LocalAbout From Slack Logs to Smart Search — Powered by MCP and Claude Desktop
This local search project lets individuals and teams query Slack export logs through Claude Desktop and a Python MCP server. It parses Slack JSON files and registers search and summary resources without uploading data to the cloud.
Key features
- 01Parse Slack JSON exports
- 02Search conversations by query
- 03Summarize channels
- 04Process data locally
Use cases
- 01Find discussions in older channels
- 02Search for a topic or term
- 03Review a channel summary
MCP support
The Python MCP server registers Slack log search and channel summaries as resources, which Claude Desktop accesses through search:// and summary:// URIs.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEFrom 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}orsummary://{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
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.