Rag Starter

by cstamigo-droid

253 downloads

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GitHub

Knowledge Base

Description

# rag-starter — chat with your documents (RAG), with citations A production-ready starter that turns a folder of documents into a **cited Q&A service**. Drop in your PDFs / Markdown / text, ask questions, get answers grounded in the source — every claim traceable to the exact…

About

Details

Author: cstamigo-droid
Downloads: 253
Categories: Knowledge Base

- Keyless by default – embeddings run locally with ONNX MiniLM; no API key needed.
- Citations, not hallucinations – every answer includes source references like [file.pdf p3].
- Optional answer synthesis – with an ANTHROPIC_API_KEY the server writes a cited answer; without one it returns passages for the host LLM.
- Idempotent ingestion – re-ingesting a file updates it in place without duplicates.
- Two interfaces from one codebase – MCP server and HTTP API.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Rag Starter

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

From the repository

Install dependencies with pip install -r requirements.txt, then either run the MCP server by adding it to claude_desktop_config.json or start the HTTP API with the rag-starter-api command. Use the provided tools (rag_ingest, rag_search, rag_answer) to index documents and ask questions.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "rag starter": {
            "rag-starter": {
                "command": "python",
                "args": [
                    "-m",
                    "rag_starter"
                ],
                "cwd": "C:/path/to/rag-starter"
            }
        }
    }
}

McpServers

{
    "rag-starter": {
        "command": "python",
        "args": [
            "-m",
            "rag_starter"
        ],
        "cwd": "C:/path/to/rag-starter"
    }
}

rag-starter — chat with your documents (RAG), with citations

A production-ready starter that turns a folder of documents into a cited Q&A
service. Drop in your PDFs / Markdown / text, ask questions, get answers grounded
in the source — every claim traceable to the exact passage it came from.

Exposed two ways from one codebase:
- MCP server — plug it into Claude Desktop / Claude Code / any MCP host and chat with your docs.
- HTTP API (FastAPI) — call it from any app.

> Built once, reskinned per client. Swap the data/ folder, tweak config.py, ship.

Why it's different

- Keyless by default. Embeddings run locally (ONNX MiniLM) — no API key, no per-query cost, runs offline. Demo it anywhere in seconds. - Citations, not hallucinations. Retrieval returns ranked passages tagged [source#chunk] / [file.pdf p3]. A missing answer returns "Not found in the documents" — never a fabricated one. - Answer synthesis is optional. With an ANTHROPIC_API_KEY it writes a cited answer for you; without one it returns passages for the host LLM to answer. Either way the RAG works. - Idempotent ingestion. Re-ingesting a file updates it in place (no duplicates).

Quickstart

pip install -r requirements.txt          # or: pip install -e .
PYTHONUTF8=1 python tests/test_smoke.py   # proves retrieval works on the sample docs

As an HTTP API

```bash rag-starter-api # uvicorn on 127.0.0.1:8000

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Description

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Details

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Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

rag-starter — chat with your documents (RAG), with citations

Why it's different

Quickstart

As an HTTP API

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