From 18e1e7959811ea0fca1140b025c1019c00da0619 Mon Sep 17 00:00:00 2001
From: Yiorgis Gozadinos <ggozadinos@gmail.com>
Date: Fri, 20 Jun 2025 10:03:00 +0200
Subject: [PATCH] Update docs

---
 README.md      | 40 +++++++++++++++++++++++++++++++---------
 pyproject.toml |  1 +
 2 files changed, 32 insertions(+), 9 deletions(-)

diff --git a/README.md b/README.md
index 9c73285b..554d4d61 100644
--- a/README.md
+++ b/README.md
@@ -7,6 +7,9 @@ A SQLite-based Retrieval-Augmented Generation (RAG) system built for efficient d
 - **Support for various embedding providers**: You can use Ollama, VoyageAI or add your own
 - **Hybrid Search**: Vector search using `sqlite-vec` combined with full-text search `FTS5`, using Reciprocal Rank Fusion
 - **Multi-format Support**: Parse 40+ file formats including PDF, DOCX, HTML, Markdown, audio and more. Or add a url!
+- **File monitoring** when run as a server automatically indexing your files
+- **MCP server** Exposes functionality as MCP tools.
+- **Python client** Call `haiku.rag` from your own python applications.
 
 ## Installation
 
@@ -21,6 +24,13 @@ For other providers use:
 
 ## Configuration
 
+You can set the directories to monitor using the `MONITOR_DIRECTORIES` environment variable (as comma separated values) :
+
+```bash
+# Monitor single directory
+export MONITOR_DIRECTORIES="/path/to/documents,/another_path/to/documents"
+```
+
 If you want to use an alternative embeddings provider (Ollama being the default) you will need to set the provider details through environment variables:
 
 By default:
@@ -67,7 +77,7 @@ haiku-rag search "machine learning"
 # Search with custom options
 haiku-rag search "python programming" --limit 10 --k 100
 
-# Start MCP server (default HTTP transport)
+# Start file monitoring & MCP server (default HTTP transport)
 haiku-rag serve # --stdio for stdio transport or --sse for SSE transport
 ```
 
@@ -77,7 +87,26 @@ haiku-rag command -h
 ```
 to see additional parameters for a command.
 
-## MCP Server
+## File Monitoring & MCP server
+
+You can start the server (using Streamble HTTP, stdio or SSE transports) with:
+
+```bash
+# Start with default HTTP transport
+haiku-rag serve # --stdio for stdio transport or --sse for SSE transport
+```
+
+You need to have set the `MONITOR_DIRECTORIES` environment variable for monitoring to take place.
+
+### File monitoring
+
+`haiku.rag` can watch directories for changes and automatically update the document store:
+
+- **Startup**: Scan all monitored directories and add any new files
+- **File Added/Modified**: Automatically parse and add/update the document in the database
+- **File Deleted**: Remove the corresponding document from the database
+
+### MCP Server
 
 `haiku.rag` includes a Model Context Protocol (MCP) server that exposes RAG functionality as tools for AI assistants like Claude Desktop. The MCP server provides the following tools:
 
@@ -89,13 +118,6 @@ to see additional parameters for a command.
 - `list_documents` - List all documents with pagination
 - `delete_document` - Delete documents by ID
 
-You can start the server (using Streamble HTTP, stdio or SSE transports) with:
-
-```bash
-# Start with default HTTP transport
-haiku-rag serve # --stdio for stdio transport or --sse for SSE transport
-```
-
 ## Using `haiku.rag` from python
 
 ### Managing documents
diff --git a/pyproject.toml b/pyproject.toml
index 9fc68928..68dd2c0a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -6,6 +6,7 @@ authors = [{ name = "Yiorgis Gozadinos", email = "ggozadinos@gmail.com" }]
 license = { text = "MIT" }
 readme = { file = "README.md", content-type = "text/markdown" }
 requires-python = ">=3.10"
+keywords = ["RAG", "sqlite", "sqlite-vec", "ml", "mcp"]
 classifiers = [
     "Development Status :: 4 - Beta",
     "Environment :: Console",