What are the prerequisites to run MCP-RAG?
You need to install `uv` and have Python available. API keys for Anthropic, Slack (bot token and team ID), and Brave Search are required.
@kira1228
基本情報
AI-powered Chat System with multiple MCP servers.
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"MCP-RAG-": {
"command": "uv",
"args": [
"venv"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
MCP-RAG is an AI-powered chat system that integrates multiple MCP servers (Filesystem, Slack, Brave-Search) to enable the Claude AI to retrieve and reference information from local documents, Slack conversations, and real-time web search based on user queries. It is built for users who want a unified assistant that can seamlessly access diverse data sources.
Install uv (see README for install commands), clone the repository, create a .env file with ANTHROPIC_API_KEY, SLACK_BOT_TOKEN, SLACK_TEAM_ID, and BRAVE_API_KEY, then set up a virtual environment and install dependencies with uv venv and uv sync. Run the client using uv run client.py path/to/dir/you/want/to/use.
You need to install `uv` and have Python available. API keys for Anthropic, Slack (bot token and team ID), and Brave Search are required.
Create a `.env` file and add `ANTHROPIC_API_KEY`, `SLACK_BOT_TOKEN`, `SLACK_TEAM_ID`, and `BRAVE_API_KEY` with your credentials.
MCP-RAG can access any folder specified in the `path/to/dir/you/want/to/use` argument when running the client.
The README does not specify data storage. The system accesses files, Slack, and web services temporarily during query processing.
No transport or authentication details beyond the API tokens are provided in the README.

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