# knowledge-mcp

A Model Context Protocol (MCP) server that provides scoped RAG workspaces ("Notebooks") backed by **Qdrant** and **TEI**.

## Overview

This server enables an agent to:
1.  Create named "Notebooks" (Qdrant Collections).
2.  Ingest documents (PDF, Markdown, Text) into specific notebooks.
3.  Query specific notebooks using vector search (RAG).
4.  Synthesize findings across a notebook.

Designed to replicate the **NotebookLM** experience: clean, focused, bounded context.

## Stack
*   **Language:** Python 3.11+
*   **Framework:** `mcp` SDK
*   **Vector DB:** Qdrant
*   **Embeddings:** Text Embeddings Inference (TEI) - `BAAI/bge-base-en-v1.5`

## Tools

### `notebook.create`
Creates a new isolated workspace (Qdrant Collection).
- `name`: string (e.g., "project-alpha")

### `notebook.add_source`
Ingests a document into the notebook.
- `notebook`: string
- `url`: string (URL or local path)

### `notebook.query`
Performs a semantic search/RAG generation against the notebook.
- `notebook`: string
- `query`: string

## Configuration
Env vars:
- `QDRANT_URL`: URL to Qdrant (e.g., `http://qdrant.openshift-gitops.svc:6333`)
- `TEI_URL`: URL to TEI (e.g., `http://text-embeddings.tei.svc.cluster.local:8080`)