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

@AdilFayyaz

代码仓库

基本信息

分类

沟通协作

许可证

MIT

传输方式

stdio

作者

AdilFayyaz

关于 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

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

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

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

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

1

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.

2

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.

3

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.

4

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.”

5

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`).

评论

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