docs: make README easier to follow and update related docs (#884)

backend/docs/CONFIGURATION.md

@@ -2,35 +2,6 @@
 
 This guide explains how to configure DeerFlow for your environment.
 
-## Quick Start
-
-1. **Copy the example configuration** (from project root):
-   ```bash
-   # From project root directory (deer-flow/)
-   cp config.example.yaml config.yaml
-   ```
-
-2. **Set your API keys**:
-
-   Option A: Use environment variables (recommended):
-   ```bash
-   export OPENAI_API_KEY="your-api-key-here"
-   export ANTHROPIC_API_KEY="your-api-key-here"
-   # Add other keys as needed
-   ```
-
-   Option B: Edit `config.yaml` directly (not recommended for production):
-   ```yaml
-   models:
-     - name: gpt-4
-       api_key: your-actual-api-key-here  # Replace placeholder
-   ```
-
-3. **Start the application**:
-   ```bash
-   make dev
-   ```
-
 ## Configuration Sections
 
 ### Models
@@ -103,6 +74,32 @@ tools:
 
 ### Sandbox
 
+DeerFlow supports multiple sandbox execution modes. Configure your preferred mode in `config.yaml`:
+
+**Local Execution** (runs sandbox code directly on the host machine):
+```yaml
+sandbox:
+   use: src.sandbox.local:LocalSandboxProvider # Local execution
+```
+
+**Docker Execution** (runs sandbox code in isolated Docker containers):
+```yaml
+sandbox:
+   use: src.community.aio_sandbox:AioSandboxProvider # Docker-based sandbox
+```
+
+**Docker Execution with Kubernetes** (runs sandbox code in Kubernetes pods via provisioner service):
+
+This mode runs each sandbox in an isolated Kubernetes Pod on your **host machine's cluster**. Requires Docker Desktop K8s, OrbStack, or similar local K8s setup.
+
+```yaml
+sandbox:
+   use: src.community.aio_sandbox:AioSandboxProvider
+   provisioner_url: http://provisioner:8002
+```
+
+See [Provisioner Setup Guide](docker/provisioner/README.md) for detailed configuration, prerequisites, and troubleshooting.
+
 Choose between local execution or Docker-based isolation:
 
 **Option 1: Local Sandbox** (default, simpler setup):

backend/docs/MCP_SERVER.md

@@ -0,0 +1,34 @@
+# MCP (Model Context Protocol) Configuration
+
+DeerFlow supports configurable MCP servers and skills to extend its capabilities, which are loaded from a dedicated `extensions_config.json` file in the project root directory.
+
+## Setup
+
+1. Copy `extensions_config.example.json` to `extensions_config.json` in the project root directory.
+   ```bash
+   # Copy example configuration
+   cp extensions_config.example.json extensions_config.json
+   ```
+   
+2. Enable the desired MCP servers or skills by setting `"enabled": true`.
+3. Configure each server’s command, arguments, and environment variables as needed.
+4. Restart the application to load and register MCP tools.
+
+## How It Works
+
+MCP servers expose tools that are automatically discovered and integrated into DeerFlow’s agent system at runtime. Once enabled, these tools become available to agents without additional code changes.
+
+## Example Capabilities
+
+MCP servers can provide access to:
+
+- **File systems**
+- **Databases** (e.g., PostgreSQL)
+- **External APIs** (e.g., GitHub, Brave Search)
+- **Browser automation** (e.g., Puppeteer)
+- **Custom MCP server implementations**
+
+## Learn More
+
+For detailed documentation about the Model Context Protocol, visit:  
+https://modelcontextprotocol.io