diff --git a/README.md b/README.md
index 7d1d6126..8e20b3e1 100644
--- a/README.md
+++ b/README.md
@@ -2,6 +2,8 @@
 
 Retrieval-Augmented Generation (RAG) library on SQLite.
 
+`haiku.rag` is a Retrieval-Augmented Generation (RAG) library built to work on SQLite alone without the need for external vector databases. It uses [sqlite-vec](https://github.com/asg017/sqlite-vec) for storing the embeddings and performs semantic (vector) search as well as full-text search combined through Reciprocal Rank Fusion. Both open-source (Ollama) as well as commercial (OpenAI, VoyageAI) embedding providers are supported.
+
 ## Features
 
 - **Local SQLite**: No external servers required
diff --git a/docs/configuration.md b/docs/configuration.md
index d7cdd593..8ba6cc7e 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -1,6 +1,6 @@
 # Configuration
 
-Configuration is done through environment variables.
+Configuration is done through the use of environment variables.
 
 ## File Monitoring
 
diff --git a/docs/index.md b/docs/index.md
index c81ab0f2..404ae8b4 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,6 +1,7 @@
 # haiku.rag
 
-A Retrieval-Augmented Generation (RAG) library on SQLite.
+`haiku.rag` is a Retrieval-Augmented Generation (RAG) library built to work on SQLite alone without the need for external vector databases. It uses [sqlite-vec](https://github.com/asg017/sqlite-vec) for storing the embeddings and performs semantic (vector) search as well as full-text search combined through Reciprocal Rank Fusion. Both open-source (Ollama) as well as commercial (OpenAI, VoyageAI) embedding providers are supported.
+
 
 ## Features
 
diff --git a/docs/mcp.md b/docs/mcp.md
index 58adf7db..22f0f667 100644
--- a/docs/mcp.md
+++ b/docs/mcp.md
@@ -1,6 +1,6 @@
 # Model Context Protocol (MCP)
 
-The MCP server exposes RAG functionality as tools for AI assistants like Claude Desktop.
+The MCP server exposes `haiku.rag` as MCP tools for compatible MCP clients.
 
 ## Available Tools
 
@@ -19,7 +19,7 @@ The MCP server exposes RAG functionality as tools for AI assistants like Claude
 
 ## Starting MCP Server
 
-The MCP server starts automatically with the serve command:
+The MCP server starts automatically with the serve command and supports `Streamable HTTP`, `stdio` and `SSE` transports:
 
 ```bash
 # Default HTTP transport
@@ -31,10 +31,3 @@ haiku-rag serve --stdio
 # SSE transport
 haiku-rag serve --sse
 ```
-
-## Integration
-
-The MCP server follows the Model Context Protocol specification, making it compatible with:
-- Claude Desktop
-- Other MCP-compatible AI assistants
-- Custom MCP clients
diff --git a/docs/python.md b/docs/python.md
index 3b81c232..9908210e 100644
--- a/docs/python.md
+++ b/docs/python.md
@@ -92,10 +92,3 @@ for chunk, relevance_score in results:
     print(f"Content: {chunk.content}")
     print(f"From document: {chunk.document_id}")
 ```
-
-## Search Technology
-
-`haiku.rag` uses hybrid search combining:
-- **Vector search** using `sqlite-vec` for semantic similarity
-- **Full-text search** using SQLite's `FTS5` for keyword matching
-- **Reciprocal Rank Fusion** to combine and rank results