diff --git a/README.md b/README.md
index a30a81e..7a35efd 100644
--- a/README.md
+++ b/README.md
@@ -3,9 +3,33 @@
MyDuck Server
-
**MyDuck Server** unlocks serious power for your MySQL & Postgres analytics. Imagine the simplicity of (MySQL|Postgres)βs familiar interface fused with the raw analytical speed of [DuckDB](https://duckdb.org/). Now you can supercharge your analytical queries with DuckDBβs lightning-fast OLAP engine, all while using the tools and dialect you know.
+
+
+
+
+## π Table of Contents
+
+- [Why MyDuck](#β-why-myduck-β)
+- [Key Features](#β¨-key-features)
+- [Performance](#π-performance)
+- [Getting Started](#πββοΈ-getting-started)
+ - [Prerequisites](#prerequisites)
+ - [Installation](#installation)
+ - [Usage](#usage)
+ - [Replicating Data](#replicating-data)
+ - [Connecting to Cloud MySQL & Postgres](#connecting-to-cloud-mysql--postgres)
+ - [HTAP Setup](#htap-setup)
+ - [Query Parquet Files](#query-parquet-files)
+ - [Already Using DuckDB?](#already-using-duckdb)
+ - [LLM Integration](#llm-integration)
+ - [Access from Python](#access-from-python)
+- [Roadmap](#π―-roadmap)
+- [Contributing](#π‘-contributing)
+- [Acknowledgements](#π-acknowledgements)
+- [License](#π-license)
+
## β Why MyDuck β
While MySQL and Postgres are the most popular open-source databases for OLTP, their performance in analytics often falls short. DuckDB, on the other hand, is built for fast, embedded analytical processing. MyDuck Server lets you enjoy DuckDB's high-speed analytics without leaving the (MySQL|Postgres) ecosystem.
@@ -24,9 +48,6 @@ MyDuck Server isn't here to replace MySQL & Postgres β it's here to help MySQL
## β¨ Key Features
-
-
-
- **Blazing Fast OLAP with DuckDB**: MyDuck stores data in DuckDB, an OLAP-optimized database known for lightning-fast analytical queries. DuckDB enables MyDuck to execute queries up to 1000x faster than traditional MySQL & Postgres setups, making complex analytics practical that were previously unfeasible.
@@ -56,16 +77,6 @@ MyDuck Server isn't here to replace MySQL & Postgres β it's here to help MySQL
Typical OLAP queries can run **up to 1000x faster** with MyDuck Server compared to MySQL & Postgres alone, especially on large datasets. Under the hood, it's just DuckDB doing what it does best: processing analytical queries at lightning speed. You are welcome to run your own benchmarks and prepare to be amazed! Alternatively, you can refer to well-known benchmarks like the [ClickBench](https://benchmark.clickhouse.com/) and [H2O.ai db-benchmark](https://duckdblabs.github.io/db-benchmark/) to see how DuckDB performs against other databases and data science tools. Also remember that DuckDB has robust support for transactions, JOINs, and [larger-than-memory query processing](https://duckdb.org/2024/07/09/memory-management.html), which are unavailable in many competing systems and tools.
-## π― Roadmap
-
-We have big plans for MyDuck Server! Here are some of the features weβre working on:
-
-- [x] Be compatible with MySQL proxy tools like [ProxySQL](https://proxysql.com/).
-- [x] Replicate data from PostgreSQL.
-- [ ] Authentication.
-- [ ] ...and more! Weβre always looking for ways to make MyDuck Server better. If you have a feature request, please let us know by [opening an issue](https://github.com/apecloud/myduckserver/issues/new).
-
-
## πββοΈ Getting Started
### Prerequisites
@@ -140,7 +151,7 @@ With MyDuck's powerful analytics capabilities, you can create an hybrid transact
* Provisioning a MySQL HTAP cluster based on [ProxySQL](docs/tutorial/mysql-htap-proxysql-setup.md) or [MariaDB MaxScale](docs/tutorial/mysql-htap-maxscale-setup.md).
* Provisioning a PostgreSQL HTAP cluster based on [PGPool-II](docs/tutorial/pg-htap-pgpool-setup.md)
-### Query & Load Parquet Files
+### Query Parquet Files
Looking to load Parquet files into MyDuck Server and start querying? Follow our [Parquet file loading guide](docs/tutorial/load-parquet-files.md) for easy setup.
@@ -148,6 +159,23 @@ Looking to load Parquet files into MyDuck Server and start querying? Follow our
Already have a DuckDB file? You can seamlessly bootstrap MyDuck Server with it. See our [DuckDB file bootstrapping guide](docs/tutorial/bootstrap.md) for more details.
+### LLM Integration
+
+MyDuck Server can be integrated with LLM applications via the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction). Follow the [MCP integration guide](docs/tutorial/mcp.md) to set up MyDuck Server as an external data source for LLMs.
+
+### Access from Python
+
+MyDuck Server can be seamlessly accessed from the Python data science ecosystem. Follow the [Python integration guide](docs/tutorial/pg-python-data-tools.md) to connect to MyDuck Server from Python and export data to PyArrow, pandas, and Polars. Additionally, check out the [Ibis integration guide](docs/tutorial/connect-with-ibis-setup.md) for using the [Ibis](https://ibis-project.org/) dataframe API to query MyDuck Server directly.
+
+## π― Roadmap
+
+We have big plans for MyDuck Server! Here are some of the features weβre working on:
+
+- [x] Be compatible with MySQL proxy tools like [ProxySQL](https://proxysql.com/).
+- [x] Replicate data from PostgreSQL.
+- [ ] Authentication.
+- [ ] ...and more! Weβre always looking for ways to make MyDuck Server better. If you have a feature request, please let us know by [opening an issue](https://github.com/apecloud/myduckserver/issues/new).
+
## π‘ Contributing
Letβs make MySQL & Postgres analytics fast and powerful β together!