What is Md Rag Mcp

md-rag-mcp is a Retrieval-Augmented Generation (RAG) system designed to index markdown (md) files accessible via an MCP server. It facilitates semantic search and interaction with AI agents.

Use cases

Use cases include personal journaling for self-reflection, academic research for retrieving information from notes, and enhancing AI agents with contextual knowledge from user-generated content.

How to use

To use md-rag-mcp, add your daily journal entries in the specified directory structure. Activate the Python virtual environment and run the rag_search.py script to index and search your entries semantically.

Key features

Key features include semantic search capabilities, an organized directory structure for journal entries, and integration with an MCP server for enhanced AI interactions.

Where to use

md-rag-mcp can be used in personal journaling, research documentation, and any scenario where structured text needs to be indexed and searched semantically.

Journal RAG System

This repository contains the code for a journal Retrieval-Augmented Generation (RAG) system. This code was used for the journal published at https://dev.to/lord_magus/supercharging-my-vs-code-ai-agent-with-local-rag-25n8.

Directory Structure

The project is organized with a focus on journaling, with technical components hidden:

/
├── README.md                 # Project overview
├── journal/                  # Journal entries
│   ├── 2025/                 # Organized by year
│   │   └── 04/               # Month
│   │       ├── 18.md         # Daily entries
│   │       └── 19.md
│   └── topics/               # Topic-based entries (future use)
├── code/                     # Code and scripts
│   ├── mcp/                  # MCP server code
│   │   └── journal_rag_mcp.py
│   ├── scripts/              # Python scripts
│   │   └── rag_search.py
│   └── data/                 # Data storage (e.g., vector DB)
│       └── chroma_db/        # Vector database (example)
└── .venv/                    # Python virtual environment

Usage

Journaling

Add daily journal entries in the journal/YYYY/MM/ directory structure.
Note: The .md files currently present in the journal/ directory are AI-generated examples provided for testing the indexing and querying functionality.

RAG Search

To search your journal using semantic search:

source .venv/bin/activate
python .tech/code/scripts/rag_search.py

This will index all your journal entries recursively and allow you to search them semantically using natural language queries. For detailed setup steps, please refer to install_instructions.md.

MCP Server

This repository also includes the code for an MCP server. This server allows you to connect your journal RAG system to an AI agent for enhanced interaction. Detailed instructions for setting up and connecting the MCP server can be found in install_instructions.md.