diff --git a/README.md b/README.md
index 694f801..0fb37c7 100644
--- a/README.md
+++ b/README.md
@@ -14,189 +14,233 @@
 
 Transform medical data analysis with AI! Ask questions about MIMIC-IV data in plain English and get instant insights. Choose between local demo data (free) or full cloud dataset (BigQuery).
 
-## ✨ Features
+## Features
 
-- 🔍 **Natural Language Queries**: Ask questions about MIMIC-IV data in plain English
-- 🏠 **Local SQLite**: Fast queries on demo database (free, no setup)
-- ☁️ **BigQuery Support**: Access full MIMIC-IV dataset on Google Cloud
-- 🔒 **Enterprise Security**: OAuth2 authentication with JWT tokens and rate limiting
-- 🛡️ **SQL Injection Protection**: Read-only queries with comprehensive validation
+- **Natural Language Queries**: Ask questions about MIMIC-IV data in plain English
+- **Local SQLite**: Fast queries on demo database (free, no setup)
+- **BigQuery Support**: Access full MIMIC-IV dataset on Google Cloud
+- **Enterprise Security**: OAuth2 authentication with JWT tokens and rate limiting
+- **SQL Injection Protection**: Read-only queries with comprehensive validation
 
 ## 🚀 Quick Start
 
-> 💡 **Need more options?** Run `m3 --help` to see all available commands and options.
+> 📺 **Prefer video tutorials?** Check out [step-by-step video guides](https://rafiattrach.github.io/m3/) covering setup, PhysioNet configuration, and more.
 
-### 📦 Installation
+### Install uv (required for `uvx`)
 
-Choose your preferred installation method:
+We use `uvx` to run the MCP server. Install `uv` from the official installer, then verify with `uv --version`.
 
-#### Option A: Install from PyPI (Recommended)
-
-**Step 1: Create Virtual Environment**
+**macOS and Linux:**
 ```bash
-# Create virtual environment (recommended)
-python -m venv .venv
-source .venv/bin/activate  # Windows: .venv\Scripts\activate
+curl -LsSf https://astral.sh/uv/install.sh | sh
+```
+
+**Windows (PowerShell):**
+```powershell
+powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
 ```
 
-**Step 2: Install M3**
+Verify installation:
 ```bash
-# Install M3
-pip install m3-mcp
+uv --version
 ```
 
-#### Option B: Docker
+### BigQuery Setup (Optional - Full Dataset)
 
-```bash
-# Clone repo first
-git clone https://github.com/rafiattrach/m3.git && cd m3
+**Skip this if using SQLite demo database.**
 
-# SQLite (demo DB)
-docker build -t m3:lite --target lite .
-docker run -d --name m3-server m3:lite tail -f /dev/null
+1. **Install Google Cloud SDK:**
+   - macOS: `brew install google-cloud-sdk`
+   - Windows/Linux: https://cloud.google.com/sdk/docs/install
 
-# BigQuery (full dataset - requires GCP credentials)
-docker build -t m3:bigquery --target bigquery .
-docker run -d --name m3-server \
-  -e M3_BACKEND=bigquery \
-  -e M3_PROJECT_ID=YOUR_PROJECT_ID \
-  -v $HOME/.config/gcloud:/root/.config/gcloud:ro \
-  m3:bigquery tail -f /dev/null
-```
+2. **Authenticate:**
+   ```bash
+   gcloud auth application-default login
+   ```
+   *Opens your browser - choose the Google account with BigQuery access to MIMIC-IV.*
+
+### MCP Client Configuration
+
+Paste one of the following into your MCP client config, then restart your client.
+
+**Supported clients:** [Claude Desktop](https://www.claude.com/download), [Cursor](https://cursor.com/download), [Goose](https://block.github.io/goose/), and [more](https://github.com/punkpeye/awesome-mcp-clients).
+
+<table>
+<tr>
+<td width="50%">
+
+**SQLite (Demo Database)**
+
+Free, local, no setup required.
 
-**MCP client config** (Claude Desktop, LM Studio, etc.):
 ```json
 {
   "mcpServers": {
     "m3": {
-      "command": "docker",
-      "args": ["exec", "-i", "m3-server", "python", "-m", "m3.mcp_server"]
+      "command": "uvx",
+      "args": ["m3-mcp"],
+      "env": {
+        "M3_BACKEND": "sqlite"
+      }
     }
   }
 }
 ```
 
-Stop container: `docker stop m3-server && docker rm m3-server`
+*Demo database (136MB, 100 patients, 275 admissions) downloads automatically on first query.*
 
-#### Option C: Install from Source
+</td>
+<td width="50%">
 
-#### Using standard `pip`
-**Step 1: Clone and Navigate**
-```bash
-# Clone the repository
-git clone https://github.com/rafiattrach/m3.git
-cd m3
-```
+**BigQuery (Full Dataset)**
 
-**Step 2: Create Virtual Environment**
-```bash
-# Create virtual environment
-python -m venv .venv
-source .venv/bin/activate  # Windows: .venv\Scripts\activate
-```
+Requires GCP credentials and PhysioNet access.
 
-**Step 3: Install M3**
-```bash
-# Install M3
-pip install .
+```json
+{
+  "mcpServers": {
+    "m3": {
+      "command": "uvx",
+      "args": ["m3-mcp"],
+      "env": {
+        "M3_BACKEND": "bigquery",
+        "M3_PROJECT_ID": "your-project-id"
+      }
+    }
+  }
+}
 ```
 
-#### Using `UV` (Recommended)
-Assuming you have [UV](https://docs.astral.sh/uv/getting-started/installation/) installed.
+*Replace `your-project-id` with your Google Cloud project ID.*
 
-**Step 1: Clone and Navigate**
-```bash
-# Clone the repository
-git clone https://github.com/rafiattrach/m3.git
-cd m3
-```
+</td>
+</tr>
+</table>
 
-**Step 2: Create `UV` Virtual Environment**
-```bash
-# Create virtual environment
-uv venv
-```
+**That's it!** Restart your MCP client and ask:
+- "What tools do you have for MIMIC-IV data?"
+- "Show me patient demographics from the ICU"
+- "What is the race distribution in admissions?"
 
-**Step 3: Install M3**
-```bash
-uv sync
-# Do not forget to use `uv run` to any subsequent commands to ensure you're using the `uv` virtual environment
-```
+---
 
-### 🗄️ Database Configuration
+## Backend Comparison
 
-After installation, choose your data source:
+| Feature | SQLite (Demo) | BigQuery (Full) |
+|---------|---------------|-----------------|
+| **Cost** | Free | BigQuery usage fees |
+| **Setup** | Zero config | GCP credentials required |
+| **Data Size** | 100 patients, 275 admissions | 365k patients, 546k admissions |
+| **Speed** | Fast (local) | Network latency |
+| **Use Case** | Learning, development | Research, production |
 
-#### Option A: Local Demo Database (Recommended for Beginners)
+---
 
-**Perfect for learning and development - completely free!**
+## Alternative Installation Methods
 
-1. **Download demo database**:
-   ```bash
-   m3 init mimic-iv-demo
-   ```
+> Already have Docker or prefer pip? Here are other ways to run m3:
 
-2. **Setup MCP Client**:
-   ```bash
-   m3 config
-   ```
+### 🐳 Docker (No Python Required)
 
-   *Alternative: For Claude Desktop specifically:*
-   ```bash
-   m3 config claude
-   ```
+<table>
+<tr>
+<td width="50%">
 
-3. **Restart your MCP client** and ask:
+**SQLite:**
+```bash
+git clone https://github.com/rafiattrach/m3.git && cd m3
+docker build -t m3:lite --target lite .
+docker run -d --name m3-server m3:lite tail -f /dev/null
+```
 
-   - "What tools do you have for MIMIC-IV data?"
-   - "Show me patient demographics from the ICU"
+</td>
+<td width="50%">
 
-#### Option B: BigQuery (Full Dataset)
+**BigQuery:**
+```bash
+git clone https://github.com/rafiattrach/m3.git && cd m3
+docker build -t m3:bigquery --target bigquery .
+docker run -d --name m3-server \
+  -e M3_BACKEND=bigquery \
+  -e M3_PROJECT_ID=your-project-id \
+  -v $HOME/.config/gcloud:/root/.config/gcloud:ro \
+  m3:bigquery tail -f /dev/null
+```
 
-**For researchers needing complete MIMIC-IV data**
+</td>
+</tr>
+</table>
 
-##### Prerequisites
-- Google Cloud account and project with billing enabled
-- Access to MIMIC-IV on BigQuery (requires PhysioNet credentialing)
+**MCP config (same for both):**
+```json
+{
+  "mcpServers": {
+    "m3": {
+      "command": "docker",
+      "args": ["exec", "-i", "m3-server", "python", "-m", "m3.mcp_server"]
+    }
+  }
+}
+```
 
-##### Setup Steps
+Stop: `docker stop m3-server && docker rm m3-server`
 
-1. **Install Google Cloud CLI**:
+### pip Install + CLI Tools
 
-   **macOS (with Homebrew):**
-   ```bash
-   brew install google-cloud-sdk
-   ```
+```bash
+pip install m3-mcp
+```
 
-   **Windows:** Download from https://cloud.google.com/sdk/docs/install
+> 💡 **CLI commands:** Run `m3 --help` to see all available options.
 
-   **Linux:**
-   ```bash
-   curl https://sdk.cloud.google.com | bash
-   ```
+**Useful CLI commands:**
+- `m3 init mimic-iv-demo` - Download demo database
+- `m3 config` - Generate MCP configuration interactively
+- `m3 config claude --backend bigquery --project-id YOUR_PROJECT_ID` - Quick BigQuery setup
 
-2. **Authenticate**:
-   ```bash
-   gcloud auth application-default login
-   ```
-   *This will open your browser - choose the Google account that has access to your BigQuery project with MIMIC-IV data.*
+**Example MCP config:**
+```json
+{
+  "mcpServers": {
+    "m3": {
+      "command": "m3-mcp-server",
+      "env": {
+        "M3_BACKEND": "sqlite"
+      }
+    }
+  }
+}
+```
 
-3. **Setup MCP Client for BigQuery**:
-   ```bash
-   m3 config
-   ```
+### Local Development
 
-   *Alternative: For Claude Desktop specifically:*
-   ```bash
-   m3 config claude --backend bigquery --project-id YOUR_PROJECT_ID
-   ```
+For contributors:
 
-4. **Test BigQuery Access** - Restart your MCP client and ask:
-   ```
-   Use the get_race_distribution function to show me the top 5 races in MIMIC-IV admissions.
-   ```
+```bash
+git clone https://github.com/rafiattrach/m3.git && cd m3
+python -m venv .venv
+source .venv/bin/activate  # Windows: .venv\Scripts\activate
+pip install -e ".[dev]"
+pre-commit install
+```
+
+**MCP config:**
+```json
+{
+  "mcpServers": {
+    "m3": {
+      "command": "/path/to/m3/.venv/bin/python",
+      "args": ["-m", "m3.mcp_server"],
+      "cwd": "/path/to/m3",
+      "env": {
+        "M3_BACKEND": "sqlite"
+      }
+    }
+  }
+}
+```
 
-## 🔧 Advanced Configuration
+## Advanced Configuration
 
 Need to configure other MCP clients or customize settings? Use these commands:
 
@@ -218,7 +262,7 @@ m3 config --quick --backend sqlite --db-path /path/to/database.db
 m3 config --output my_config.json
 ```
 
-### 🔐 OAuth2 Authentication (Optional)
+### OAuth2 Authentication (Optional)
 
 For production deployments requiring secure access to medical data:
 
@@ -245,21 +289,9 @@ m3 config  # Choose OAuth2 option during setup
 
 > 📖 **Complete OAuth2 Setup Guide**: See [`docs/OAUTH2_AUTHENTICATION.md`](docs/OAUTH2_AUTHENTICATION.md) for detailed configuration, troubleshooting, and production deployment guidelines.
 
-### Backend Comparison
-
-**SQLite Backend (Default)**
-- ✅ **Free**: No cloud costs
-- ✅ **Fast**: Local queries
-- ✅ **Easy**: No authentication needed
-- ❌ **Limited**: Demo dataset only (~1k records)
-
-**BigQuery Backend**
-- ✅ **Complete**: Full MIMIC-IV dataset (~500k admissions)
-- ✅ **Scalable**: Google Cloud infrastructure
-- ✅ **Current**: Latest MIMIC-IV version (3.1)
-- ❌ **Costs**: BigQuery usage fees apply
+---
 
-## 🛠️ Available MCP Tools
+## Available MCP Tools
 
 When your MCP client processes questions, it uses these tools automatically:
 
@@ -270,7 +302,7 @@ When your MCP client processes questions, it uses these tools automatically:
 - **get_lab_results**: Laboratory test results
 - **get_race_distribution**: Patient race distribution
 
-## 🧪 Example Prompts
+## Example Prompts
 
 Try asking your MCP client these questions:
 
@@ -291,12 +323,7 @@ Try asking your MCP client these questions:
 - `Prompt:` *What tables are available in the database?*
 - `Prompt:` *What tools do you have for MIMIC-IV data?*
 
-## 🎩 Pro Tips
-
-- Do you want to pre-approve the usage of all tools in Claude Desktop? Use the prompt below and then select **Always Allow**
-   - `Prompt:` *Can you please call all your tools in a logical sequence?*
-
-## 🔍 Troubleshooting
+## Troubleshooting
 
 ### Common Issues
 
@@ -350,59 +377,11 @@ gcloud auth application-default login
 gcloud auth list
 ```
 
-## 👩‍💻 For Developers
-
-### Development Setup
-
-#### Option A: Standard `pip` Development Setup
-**Step 1: Clone and Navigate**
-```bash
-# Clone the repository
-git clone https://github.com/rafiattrach/m3.git
-cd m3
-```
-
-**Step 2: Create and Activate Virtual Environment**
-```bash
-# Create virtual environment
-python -m venv .venv
-source .venv/bin/activate  # Windows: .venv\Scripts\activate
-```
-
-**Step 3: Install Development Dependencies**
-```bash
-# Install in development mode with dev dependencies
-pip install -e ".[dev]"
-# Install pre-commit hooks
-pre-commit install
-```
-
-#### Option B: Development Setup with `UV` (Recommended)
-**Step 1: Clone and Navigate**
-```bash
-# Clone the repository
-git clone https://github.com/rafiattrach/m3.git
-cd m3
-```
-
-**Step 2: Create and Activate `UV` Virtual Environment**
-```bash
-# Create virtual environment
-uv venv
-```
-
-**Step 3: Install Development Dependencies**
-```bash
-# Install in development mode with dev dependencies (by default, UV runs in editable mode)
-uv sync
+## For Developers
 
-# Install pre-commit hooks
-uv run pre-commit install
-
-# Do not forget to use `uv run` to any subsequent commands to ensure you're using the `uv` virtual environment
-```
+> See "Local Development" section above for setup instructions.
 
-### Testing
+### Running Tests
 
 ```bash
 pytest  # All tests (includes OAuth2 and BigQuery mocks)
@@ -428,15 +407,15 @@ export M3_OAUTH2_TOKEN="Bearer your-test-token"
 m3-mcp-server
 ```
 
-## 🔮 Roadmap
+## Roadmap
 
-- 🏠 **Local Full Dataset**: Complete MIMIC-IV locally (no cloud costs)
-- 🔧 **Advanced Tools**: More specialized medical data functions
-- 📊 **Visualization**: Built-in plotting and charting tools
-- 🔐 **Enhanced Security**: Role-based access control, audit logging
-- 🌐 **Multi-tenant Support**: Organization-level data isolation
+- **Local Full Dataset**: Complete MIMIC-IV locally (no cloud costs)
+- **Advanced Tools**: More specialized medical data functions
+- **Visualization**: Built-in plotting and charting tools
+- **Enhanced Security**: Role-based access control, audit logging
+- **Multi-tenant Support**: Organization-level data isolation
 
-## 🤝 Contributing
+## Contributing
 
 We welcome contributions! Please:
 
@@ -445,6 +424,28 @@ We welcome contributions! Please:
 3. Add tests for new functionality
 4. Submit a pull request
 
+## Citation
+
+If you use M3 in your research, please cite:
+
+```bibtex
+@article{attrach2025conversational,
+  title={Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis},
+  author={Attrach, Rafi Al and Moreira, Pedro and Fani, Rajna and Umeton, Renato and Celi, Leo Anthony},
+  journal={arXiv preprint arXiv:2507.01053},
+  year={2025}
+}
+```
+
+You can also use the "Cite this repository" button at the top of the GitHub page for other formats.
+
+## Related Projects
+
+M3 has been forked and adapted by the community:
+- [MCPStack-MIMIC](https://github.com/MCP-Pipeline/mcpstack-mimic) - Integrates M3 with other MCP servers (Jupyter, sklearn, etc.)
+
+---
+
 *Built with ❤️ for the medical AI community*
 
 **Need help?** Open an issue on GitHub or check our troubleshooting guide above.
diff --git a/llms-install.md b/llms-install.md
new file mode 100644
index 0000000..d5480ea
--- /dev/null
+++ b/llms-install.md
@@ -0,0 +1,95 @@
+# M3 MCP Server - Installation Guide for AI Agents
+
+This guide helps AI agents like Cline install and configure the M3 MCP server.
+
+## Installation Method
+
+Use `uvx` for zero-installation setup:
+
+```bash
+uvx m3-mcp
+```
+
+## Backend Configuration
+
+M3 supports two backends. Choose one:
+
+### Option 1: SQLite (Demo Database - Recommended for Testing)
+
+**MCP Configuration:**
+```json
+{
+  "mcpServers": {
+    "m3": {
+      "command": "uvx",
+      "args": ["m3-mcp"],
+      "env": {
+        "M3_BACKEND": "sqlite"
+      }
+    }
+  }
+}
+```
+
+**Features:**
+- No setup required
+- Demo database (100 patients, 275 admissions) downloads automatically
+- Perfect for testing and development
+
+### Option 2: BigQuery (Full MIMIC-IV Dataset)
+
+**Prerequisites:**
+1. User must have Google Cloud credentials configured
+2. User must have access to MIMIC-IV on BigQuery (requires PhysioNet credentialing)
+
+**MCP Configuration:**
+```json
+{
+  "mcpServers": {
+    "m3": {
+      "command": "uvx",
+      "args": ["m3-mcp"],
+      "env": {
+        "M3_BACKEND": "bigquery",
+        "M3_PROJECT_ID": "user-project-id"
+      }
+    }
+  }
+}
+```
+
+**Setup Steps:**
+1. Install Google Cloud SDK: `brew install google-cloud-sdk` (macOS)
+2. Authenticate: `gcloud auth application-default login`
+3. Replace `user-project-id` with the user's actual GCP project ID
+
+## Verification
+
+After configuration, test by asking:
+- "What tools do you have for MIMIC-IV data?"
+- "Show me patient demographics from the ICU"
+
+## Troubleshooting
+
+**If SQLite backend fails:**
+- The demo database downloads automatically on first query
+- No manual `m3 init` needed
+
+**If BigQuery backend fails:**
+- Verify GCP authentication: `gcloud auth list`
+- Confirm PhysioNet access to MIMIC-IV dataset
+- Check project ID is correct
+
+## Available Tools
+
+- `get_database_schema` - List available tables
+- `get_table_info` - Get column info and sample data
+- `execute_mimic_query` - Execute SQL queries
+- `get_icu_stays` - ICU stay information
+- `get_lab_results` - Laboratory test results
+- `get_race_distribution` - Patient demographics
+
+## Additional Resources
+
+- Full documentation: https://github.com/rafiattrach/m3
+- Video tutorials: https://rafiattrach.github.io/m3/
diff --git a/pyproject.toml b/pyproject.toml
index 923035b..66269dc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -64,7 +64,8 @@ dev = [
 
 [project.scripts]
 m3 = "m3.cli:app"
-m3-mcp-server = "m3.mcp_server:main"
+m3-mcp = "m3.mcp_server:main"  # Primary entry point for simplicity (enables `uvx m3-mcp`)
+m3-mcp-server = "m3.mcp_server:main"  # Kept for backwards compatibility
 
 [project.urls]
 Homepage = "https://github.com/rafiattrach/m3"
diff --git a/src/m3/__init__.py b/src/m3/__init__.py
index 393f13d..c2c0b88 100644
--- a/src/m3/__init__.py
+++ b/src/m3/__init__.py
@@ -2,4 +2,4 @@
 MIMIC-IV + MCP + Models (M3): Local MIMIC-IV querying with LLMs via Model Context Protocol
 """
 
-__version__ = "0.2.0"
+__version__ = "0.3.0"