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MCP RAG

@kira1228

Repository

Basic information

Category

Memory & Knowledge

License

MIT

Transports

stdio

Author

kira1228

About MCP RAG

AI-powered Chat System with multiple MCP servers.

#mathgpt#math-solver#math-assistant

MCP RAG config

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

{
  "mcpServers": {
    "MCP-RAG-": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

MCP RAG tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

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

Overview

What is MCP-RAG?

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.

How to use MCP-RAG?

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.

Key features of MCP-RAG

  • Integrates Filesystem, Slack, and Brave Search MCP servers.
  • Claude automatically selects the right data source per query.
  • No explicit instructions needed from the user.
  • Access local folders, Slack history, and live web results.
  • Simple setup with environment variables and one command to run.

Use cases of MCP-RAG

  • Search and retrieve information from specified local folders.
  • Access and reference Slack conversations and channels.
  • Perform real-time web searches for current information.
  • Use a single chat interface for documents, team chat, and internet queries.

Frequently asked questions

1

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.

2

How do I set up the required API keys?

Create a `.env` file and add `ANTHROPIC_API_KEY`, `SLACK_BOT_TOKEN`, `SLACK_TEAM_ID`, and `BRAVE_API_KEY` with your credentials.

3

Which local files can be accessed?

MCP-RAG can access any folder specified in the `path/to/dir/you/want/to/use` argument when running the client.

4

Does MCP-RAG store any data?

The README does not specify data storage. The system accesses files, Slack, and web services temporarily during query processing.

5

What transport or authentication does MCP-RAG use?

No transport or authentication details beyond the API tokens are provided in the README.

Comments

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