# MCP-RAGNAR - a local RAG MCP Server

A local MCP server that implements RAG (Retrieval-Augmented Generation) with sentence window retrieval.

## Features

- Document indexing with support for multiple file types (txt, md, pdf, doc, docx)
- Sentence window retrieval for better context understanding
- Configurable embedding models (OpenAI or local hugging face mode - i.e BAAI/bge-large-en-v1.5)
- MCP server integration for easy querying

## Requirements

- Python 3.10+
- UV package manager

## Installation

1. Clone the repository:
```bash
git clone <repository-url>
cd mcp-ragnar
```

2. Install dependencies using UV:
```bash
uv pip install -e .
```

## Usage

### Indexing Documents

You can index documents either programmatically or via the command line.

#### Indexing

```bash
python -m indexer.index /path/to/documents /path/to/index

# to change the default local embedding model and chunk size
python -m indexer.index /path/to/documents /path/to/index --chunk-size=512 --embed-model BAAI/bge-small-en-v1.5

# With OpenAI embedding endpoint (put your OPENAI_API_KEY in env)
python -m indexer.index /path/to/documents /path/to/index --embed-endpoint https://api.openai.com/v1 --embed-model text-embedding-3-small --tokenizer-model o200k_base

# Get help
python -m indexer.index --help
```

### Running the MCP Server

### Configuration

can be supplied as env var or .env file

- `EMBED_ENDPOINT`: (Optional) Path to an OpenAI compatible embedding endpoint (ends with /v1). If not set, a local Hugging Face model is used by default.
- `EMBED_MODEL`: (Optional) Name of the embedding model to use. Default value of BAAI/bge-large-en-v1.5.
- `INDEX_ROOT`: The root directory for the index, used by the retriever. This is mandatory for MCP (Multi-Cloud Platform) querying.
- `MCP_DESCRIPTION`: The exposed name and description for the MCP server, used for MCP querying only. This is mandatory for MCP querying. For example: "RAG to my local personal documents"
- `INDEX_ROOT`: the root path of the index 

## in SSE mode it will listen to http://localhost:8001/ragnar
```shell
python server/sse.py
```

## in stdio mode

install locally as an uv tool
```shell
uv tool install .
```


### Claude Desktop:

Update the following:

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`

On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

Example :

```json
{
  "mcpServers": {
    "mcp-ragnar": {
      "command": "uvx",
      "args": [
        "mcp-ragnar"
      ],
      "env": {
        "OPENAI_API_KEY": "",
        "EMBED_ENDPOINT": "https://api.openai.com/v1",
        "EMBED_MODEL": "text-embedding-3-small",
        "MCP_DESCRIPTION": "My local Rust documentation",
        "INDEX_ROOT": "/tmp/index"
      }
    }
  }
}
```

## License

GNU General Public License v3.0