diff --git a/.wordlist.txt b/.wordlist.txt
index 930132b..aa0d7d7 100644
--- a/.wordlist.txt
+++ b/.wordlist.txt
@@ -664,6 +664,27 @@ Addon
 addon
 LoadBalancer
 NodePort
+Rust
+genai
+supervisord
+entrypoint
+cargo
+gpt
+mini
+RESTful
+OpenAPI
+Swagger
+npx
+modelcontextprotocol
+inspector
+nc
+openai
+rustup
+proto
+tlsv
+sSf
+AMD64
+ARM64
 orphaned
 replicas
 SQL's
diff --git a/genai-tools/index.md b/genai-tools/index.md
index 8622006..97f1bd5 100644
--- a/genai-tools/index.md
+++ b/genai-tools/index.md
@@ -24,3 +24,4 @@ FalkorDB provides powerful tools and integrations for building intelligent GenAI
 - [LangGraph](./langgraph.md): Build stateful, multi-actor agentic applications with LangGraph.
 - [LlamaIndex](./llamaindex.md): Simplify development of LLM-powered applications with LlamaIndex.
 - [GraphRAG Toolkit](./graphrag-toolkit.md): AWS GraphRAG Toolkit integration for building knowledge graph applications.
+- [Text-to-Cypher](./text-to-cypher.md): Convert natural language to Cypher queries using AI-powered text-to-cypher service.
diff --git a/genai-tools/text-to-cypher.md b/genai-tools/text-to-cypher.md
new file mode 100644
index 0000000..f38c6e0
--- /dev/null
+++ b/genai-tools/text-to-cypher.md
@@ -0,0 +1,440 @@
+---
+title: "Text-to-Cypher"
+nav_order: 7
+description: "Convert natural language to Cypher queries using AI-powered text-to-cypher service."
+parent: "GenAI Tools"
+---
+
+# Text-to-Cypher
+
+A high-performance Rust-based API service that translates natural language text to Cypher queries for graph databases, featuring integration with genai and FalkorDB. Complete all-in-one Docker solution with integrated FalkorDB database, web browser interface, text-to-cypher API, and Model Context Protocol (MCP) server support!
+
+## What's New
+
+**All-in-One Docker Solution**: Our latest Docker image now includes everything you need in a single container:
+
+- 🗄️ **FalkorDB Database** (port 6379) - Full graph database with Redis protocol
+- 🌐 **FalkorDB Web Interface** (port 3000) - Interactive graph browser and query builder  
+- 🚀 **Text-to-Cypher API** (port 8080) - Natural language to Cypher conversion
+- 🤖 **MCP Server** (port 3001) - AI assistant integration support
+
+No more complex setup - just run one Docker command and get a complete graph database stack!
+
+## Features
+
+- **Text to Cypher Translation**: Convert natural language queries to Cypher database queries using AI
+- **Graph Schema Discovery**: Automatically discover and analyze graph database schemas
+- **RESTful API**: Clean HTTP API with comprehensive OpenAPI/Swagger documentation
+- **MCP Server**: Model Context Protocol server for AI assistant integrations
+- **Streaming Responses**: Real-time Server-Sent Events (SSE) streaming of query processing results
+- **Integrated FalkorDB**: Built-in FalkorDB graph database with web browser interface
+- **All-in-One Docker Solution**: Complete stack in a single container - database, web UI, API, and MCP server
+- **AI Model Integration**: Powered by genai for natural language processing with support for multiple providers
+- **Environment Configuration**: Flexible configuration via `.env` file with fallback to request parameters
+- **Production Ready**: Comprehensive error handling, logging, and robust architecture
+- **Multi-Platform Support**: Docker images available for both AMD64 and ARM64 architectures
+
+## Quick Start
+
+### Using Docker (Recommended)
+
+The easiest way to get started is using our all-in-one Docker image that includes FalkorDB database, web browser interface, text-to-cypher API, and MCP server:
+
+```bash
+# Run the complete stack with all services
+docker run -p 6379:6379 -p 3000:3000 -p 8080:8080 -p 3001:3001 \
+  -e DEFAULT_MODEL=gpt-4o-mini -e DEFAULT_KEY=your-api-key \
+  falkordb/text-to-cypher:latest
+
+# Or using environment file
+docker run -p 6379:6379 -p 3000:3000 -p 8080:8080 -p 3001:3001 \
+  --env-file .env \
+  falkordb/text-to-cypher:latest
+
+# Or mounting .env file for full MCP server functionality
+docker run -p 6379:6379 -p 3000:3000 -p 8080:8080 -p 3001:3001 \
+  -v $(pwd)/.env:/app/.env:ro \
+  falkordb/text-to-cypher:latest
+
+# Custom ports using environment variables
+docker run -p 6379:6379 -p 3000:3000 -p 9090:9090 -p 4001:4001 \
+  -e REST_PORT=9090 -e MCP_PORT=4001 \
+  -e DEFAULT_MODEL=gpt-4o-mini -e DEFAULT_KEY=your-api-key \
+  falkordb/text-to-cypher:latest
+```
+
+### Available Services
+
+Once running, access the services at:
+
+- **FalkorDB Database**: `localhost:6379` (Redis protocol)
+- **FalkorDB Web Interface**: `http://localhost:3000` (Interactive graph database browser)
+- **Text-to-Cypher API**: `http://localhost:8080` (REST API)
+- **Swagger UI**: `http://localhost:8080/swagger-ui/` (API documentation)
+- **MCP Server**: `localhost:3001` (Model Context Protocol server)
+- **OpenAPI Spec**: `http://localhost:8080/api-doc/openapi.json`
+
+### Local Development
+
+If you prefer to run locally without Docker:
+
+```bash
+# Prerequisites: You'll need FalkorDB running separately
+docker run -d -p 6379:6379 falkordb/falkordb:latest
+
+# Install Rust (if not already installed)
+curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
+
+# Clone and run the text-to-cypher service
+git clone https://github.com/FalkorDB/text-to-cypher.git
+cd text-to-cypher
+cp .env.example .env  # Edit with your configuration
+cargo run
+```
+
+The local development setup requires:
+
+- **FalkorDB instance**: Running on port 6379 (can be Docker or native)
+- **Rust environment**: For building and running the text-to-cypher service
+
+## Configuration
+
+The application supports flexible configuration via environment variables or `.env` file:
+
+### Core Settings
+
+- `DEFAULT_MODEL`: Default AI model to use (e.g., "openai:gpt-4")
+- `DEFAULT_KEY`: Default API key for the AI service
+
+### Port Configuration
+
+- `REST_PORT`: REST API server port (default: 8080)
+- `MCP_PORT`: MCP server port for AI assistant integrations (default: 3001)
+  - The MCP server provides an SSE endpoint at `/sse` on this port
+
+### Optional Settings
+
+- `FALKORDB_CONNECTION`: FalkorDB connection string (default: "falkor://127.0.0.1:6379")
+
+Create a `.env` file from the provided example:
+
+```bash
+cp .env.example .env
+# Edit .env with your preferred default model and API key
+```
+
+### MCP Server Configuration
+
+**Important**: The MCP server will only start if:
+
+1. Both `DEFAULT_MODEL` and `DEFAULT_KEY` are configured
+2. The `.env` file physically exists (not just environment variables)
+
+For Docker deployments:
+
+- Use `--env-file .env` or `-e` flags for HTTP server only (MCP server also starts if both MODEL and KEY are provided)
+- Use `-v $(pwd)/.env:/app/.env:ro` to ensure MCP server starts with mounted `.env` file
+
+## Architecture
+
+The integrated Docker solution runs four concurrent services:
+
+### FalkorDB Database (Port 6379)
+
+- Graph database server with Redis protocol compatibility
+- Stores and manages graph data structures
+- Accessible via Redis clients and graph query languages
+
+### FalkorDB Web Interface (Port 3000)
+
+- Interactive web-based graph database browser
+- Visual query builder and result visualization
+- Database administration and monitoring tools
+- Graph data exploration interface
+
+### Text-to-Cypher HTTP API (Port 8080)
+
+- Main REST API for text-to-cypher conversion
+- Swagger UI documentation at `http://localhost:8080/swagger-ui/`
+- OpenAPI specification at `http://localhost:8080/api-doc/openapi.json`
+- Supports both streaming (SSE) and non-streaming responses
+
+### MCP Server (Port 3001) - Conditional
+
+- Model Context Protocol server for AI assistant integrations
+- Provides `text_to_cypher` tool for natural language to Cypher conversion
+- **Note**: MCP server only starts if both `DEFAULT_MODEL` and `DEFAULT_KEY` are configured
+
+## MCP Server Usage
+
+The MCP server provides a standardized interface for AI assistants to convert natural language questions into Cypher queries. This enables seamless integration with AI tools that support the Model Context Protocol.
+
+### Using MCP Inspector
+
+To test and interact with the MCP server, you can use the MCP Inspector:
+
+1. **Start the text-to-cypher stack**:
+
+```bash
+docker run -p 6379:6379 -p 3000:3000 -p 8080:8080 -p 3001:3001 \
+  -e DEFAULT_MODEL=gpt-4o-mini -e DEFAULT_KEY=your-api-key \
+  falkordb/text-to-cypher:latest
+```
+
+2. **Install MCP Inspector** (if not already installed):
+
+```bash
+npx -y @modelcontextprotocol/inspector
+```
+
+3. **Connect MCP Inspector to the server**:
+   - Open MCP Inspector in your browser (typically `http://localhost:6274`)
+   - Add a new server connection with these settings:
+     - **Transport**: `stdio`
+     - **Command**: `nc`
+     - **Arguments**: `["localhost", "3001"]`
+
+   Or if using a direct connection:
+   - **Transport**: `sse`
+   - **URL**: `http://localhost:3001/sse`
+
+4. **Available Tools**:
+   The MCP server exposes the following tool:
+
+   #### `text_to_cypher`
+
+   Converts natural language questions into Cypher queries for graph databases.
+
+   **Parameters**:
+   - `graph_name` (required): Name of the graph database to query
+   - `question` (required): Natural language question to convert to Cypher
+
+   **Example Usage in MCP Inspector**:
+
+   ```json
+   {
+     "graph_name": "movies",
+     "question": "Find all actors who appeared in movies released after 2020"
+   }
+   ```
+
+5. **Example Workflow**:
+   - Select the `text_to_cypher` tool in MCP Inspector
+   - Fill in the parameters:
+     - Graph name: `"social_network"`
+     - Question: `"Who are the friends of John with more than 5 mutual connections?"`
+   - Execute the tool
+   - View the generated Cypher query and execution results
+
+**Pro Tip**: You can also interact with the FalkorDB directly through the web interface at `http://localhost:3000` to create and explore graphs visually!
+
+### Integration with AI Assistants
+
+The MCP server enables AI assistants to:
+
+- Convert natural language to Cypher queries
+- Execute queries against FalkorDB graphs
+- Provide structured responses with query results
+- Handle complex graph database interactions seamlessly
+
+### MCP Server Benefits
+
+- **Standardized Interface**: Uses the Model Context Protocol for consistent AI tool integration
+- **Streaming Support**: Real-time processing and response streaming
+- **Error Handling**: Comprehensive error messages and validation
+- **Documentation**: Auto-generated tool documentation with parameter descriptions and examples
+
+## API Usage Examples
+
+### Basic Text-to-Cypher Request
+
+```bash
+curl -X POST "http://localhost:8080/text_to_cypher" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "graph_name": "movies",
+    "chat_request": {
+      "messages": [
+        {
+          "role": "User",
+          "content": "Find all actors who appeared in movies released after 2020"
+        }
+      ]
+    },
+    "model": "gpt-4o-mini",
+    "key": "your-api-key"
+  }'
+```
+
+### Using the FalkorDB Web Interface
+
+1. **Access the web interface**: Open `http://localhost:3000` in your browser
+2. **Connect to database**: The interface automatically connects to the local FalkorDB instance
+3. **Create sample data**: Use the visual interface to create nodes and relationships
+4. **Run queries**: Test Cypher queries directly in the web interface
+5. **Export/Import**: Save your graph data or load sample datasets
+
+### Using Server-Sent Events (SSE)
+
+The API supports streaming responses for real-time progress updates:
+
+```javascript
+const eventSource = new EventSource('/text_to_cypher', {
+  method: 'POST',
+  headers: { 'Content-Type': 'application/json' },
+  body: JSON.stringify({
+    graph_name: "social_network",
+    chat_request: {
+      messages: [{ role: "User", content: "Who are John's friends?" }]
+    }
+  })
+});
+
+eventSource.onmessage = (event) => {
+  const progress = JSON.parse(event.data);
+  console.log('Progress:', progress);
+};
+```
+
+### Complete Workflow Example
+
+```bash
+# 1. Start the complete stack
+docker run -p 6379:6379 -p 3000:3000 -p 8080:8080 -p 3001:3001 \
+  -e DEFAULT_MODEL=gpt-4o-mini -e DEFAULT_KEY=your-api-key \
+  falkordb/text-to-cypher:latest
+
+# 2. Create a graph using FalkorDB web interface (http://localhost:3000)
+# Add some sample data: people, relationships, etc.
+
+# 3. Query using natural language via the API
+curl -X POST "http://localhost:8080/text_to_cypher" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "graph_name": "social_network",
+    "chat_request": {
+      "messages": [
+        {
+          "role": "User", 
+          "content": "Find all people who have more than 3 friends"
+        }
+      ]
+    },
+    "model": "gpt-4o-mini",
+    "key": "your-api-key"
+  }'
+
+# 4. Use MCP server for AI assistant integrations (port 3001)
+# Connect your AI assistant to http://localhost:3001
+```
+
+## Deployment Options
+
+### Docker Deployment (Production)
+
+The project provides an all-in-one Docker image that includes FalkorDB database, web browser interface, text-to-cypher API, and MCP server:
+
+```bash
+# Pull the latest image
+docker pull falkordb/text-to-cypher:latest
+
+# Option 1: Complete stack with all services (recommended)
+docker run -d \
+  --name text-to-cypher-stack \
+  -p 6379:6379 \
+  -p 3000:3000 \
+  -p 8080:8080 \
+  -p 3001:3001 \
+  -e DEFAULT_MODEL=gpt-4o-mini \
+  -e DEFAULT_KEY=your-api-key \
+  --restart unless-stopped \
+  falkordb/text-to-cypher:latest
+
+# Option 2: Using environment file
+docker run -d \
+  --name text-to-cypher-stack \
+  -p 6379:6379 \
+  -p 3000:3000 \
+  -p 8080:8080 \
+  -p 3001:3001 \
+  --env-file .env \
+  --restart unless-stopped \
+  falkordb/text-to-cypher:latest
+
+# Option 3: Mount .env file for full MCP functionality
+docker run -d \
+  --name text-to-cypher-stack \
+  -p 6379:6379 \
+  -p 3000:3000 \
+  -p 8080:8080 \
+  -p 3001:3001 \
+  -v $(pwd)/.env:/app/.env:ro \
+  --restart unless-stopped \
+  falkordb/text-to-cypher:latest
+
+# View logs from all services
+docker logs -f text-to-cypher-stack
+```
+
+### Docker Configuration Options
+
+| Method | All Services | Use Case |
+|--------|-------------|----------|
+| `-e DEFAULT_MODEL=... -e DEFAULT_KEY=...` | ✅ | Environment-based config |
+| `--env-file .env` | ✅ | File-based configuration |
+| `-v $(pwd)/.env:/app/.env:ro` | ✅ | Mounted configuration file |
+
+**Note**: All four services (FalkorDB database, web interface, text-to-cypher API, and MCP server) will start when both `DEFAULT_MODEL` and `DEFAULT_KEY` are configured, regardless of how the environment variables are provided.
+
+### Service Ports
+
+| Service | Port | Description |
+|---------|------|-------------|
+| FalkorDB Database | 6379 | Redis protocol access to graph database |
+| FalkorDB Web Interface | 3000 | Interactive web browser for graph exploration |
+| Text-to-Cypher HTTP API | 8080 | REST API with Swagger documentation |
+| MCP Server | 3001 | Model Context Protocol server for AI integrations |
+
+## Troubleshooting
+
+### Common Issues
+
+**Services not starting**:
+
+- Ensure all required ports (6379, 3000, 8080, 3001) are available
+- Check that `DEFAULT_MODEL` and `DEFAULT_KEY` are properly configured
+- View logs: `docker logs -f <container-name>`
+
+**MCP Server not starting**:
+
+- Verify both `DEFAULT_MODEL` and `DEFAULT_KEY` environment variables are set
+- For local builds, ensure `.env` file exists in the working directory
+
+**FalkorDB connection issues**:
+
+- The integrated FalkorDB automatically starts with the container
+- No external FalkorDB instance needed when using the Docker image
+- Database is accessible at `localhost:6379` (Redis protocol)
+
+**Web interface not accessible**:
+
+- Ensure port 3000 is properly mapped: `-p 3000:3000`
+- Try accessing `http://localhost:3000` directly
+- Check firewall settings if running on a remote server
+
+### Getting Help
+
+- **API Documentation**: `http://localhost:8080/swagger-ui/`
+- **Web Interface**: `http://localhost:3000` for graph exploration
+- **Logs**: Use `docker logs -f <container-name>` to view all service logs
+- **Issues**: Report problems at [GitHub Issues](https://github.com/FalkorDB/text-to-cypher/issues)
+
+## Resources
+
+- 🔗 [GitHub Repository](https://github.com/FalkorDB/text-to-cypher)
+- 📚 [API Documentation (Swagger)](http://localhost:8080/swagger-ui/)
+- 🐳 [Docker Hub](https://hub.docker.com/r/falkordb/text-to-cypher)
+
+## License
+
+This project is licensed under the MIT License.