[docs] Update the tool use docs

Author: Sxnan

docs/content/docs/development/tool_use.md

@@ -22,33 +22,157 @@ specific language governing permissions and limitations
 under the License.
 -->
 
+## Overview
+
+Flink Agents provides a flexible and extensible tool use mechanism. Developers can define the tool as a local Python function, or they can integrate with a remote MCP server to use the tools provided by the MCP server.
 
 ## Local Function as Tool
 
-{{< hint warning >}}
-**TODO**: How to define and use a Local Function as Tool.
+Developer can define the tool as a local Python function, and use it in either workflow agent or react agent. 
+- For workflow agent, developer defines the tool as a static method in the agent class, and use the `@tool` annotation to mark the method as a tool. 
+- For react agent, you have to register the tool to the execution environment, and then pass the tool name to the chat model descriptor when creating the ReAct agent.
+
+{{< hint info >}}
+Flink Agents uses the docstring of the tool function to generate the tool metadata. The docstring of the python function should accurately describe the tool's purpose, parameters, and return value, so that the LLM can understand the tool and use it effectively.
 {{< /hint >}}
 
-## How to Integrate with MCP Server
+Below is an example of how to define the tool as a local Python function in workflow agent:
 
-{{< hint warning >}}
-**TODO**: How to integrate with MCP Server.
-{{< /hint >}}
+```python
+class ReviewAnalysisAgent(Agent):
 
-### MCP Tools
+    @tool
+    @staticmethod
+    def notify_shipping_manager(id: str, review: str) -> None:
+        """Notify the shipping manager when product received a negative review due to
+        shipping damage.
 
-{{< hint warning >}}
-**TODO**: How to use the tools provided by MCP Server.
-{{< /hint >}}
+        Parameters
+        ----------
+        id : str
+            The id of the product that received a negative review due to shipping damage
+        review: str
+            The negative review content
+        """
+        notify_shipping_manager(id=id, review=review)
+    
+    ...
+```
 
-### MCP Prompt
+Below is an example of how to define the tool as a local Python function in react agent:
 
-{{< hint warning >}}
-**TODO**: How to use the prompts provided by MCP Server.
-{{< /hint >}}
+```python
+def notify_shipping_manager(id: str, review: str) -> None:
+    """Notify the shipping manager when product received a negative review due to
+    shipping damage.
+
+    Parameters
+    ----------
+    id : str
+        The id of the product that received a negative review due to shipping damage
+    review: str
+        The negative review content
+    """
+    ...
+
+...
+
+# Add notify shipping manager tool to the execution environment.
+agents_env.add_resource(
+    "notify_shipping_manager", Tool.from_callable(notify_shipping_manager)
+)
+
+...
+
+# Create react agent with notify shipping manager tool.
+review_analysis_react_agent = ReActAgent(
+    chat_model=ResourceDescriptor(
+        clazz=OllamaChatModelSetup,
+        tools=["notify_shipping_manager"],
+    ),
+    ...
+)
+```
+
+## Integrate with MCP Server
+
+Flink Agents supports integrating with a remote MCP server to use the resources provided by the MCP server, including tools and prompts.
+
+To use MCP server in workflow agent, developer can use `@mcp_server` annotation to declare the server.
+
+```python
+@mcp_server
+@staticmethod
+def my_mcp_server() -> MCPServer:
+    """Define MCP server connection."""
+    return MCPServer(endpoint=MCP_SERVER_ENDPOINT)
+```
+
+To use MCP server in react agent, developer can register the MCP server to the execution environment.
+
+```python
+# Register MCP server to the execution environment.
+agents_env.add_resource("my_mcp_server", MCPServer(endpoint=MCP_SERVER_ENDPOINT))
+```
+
+### Use MCP Tool and MCP Prompt
+
+The MCP tool and prompt can be used the in same way with local function tool and local prompt.
+
+If developer define a MCP server providing tool `add` and prompt `ask_sum`, they can use them when talking  with chat model.
+
+```python
+@chat_model_setup
+@staticmethod
+def math_chat_model() -> ResourceDescriptor:
+    """ChatModel using MCP prompt and tool."""
+    return ResourceDescriptor(
+        clazz=OllamaChatModelSetup,
+        connection="ollama_connection",
+        model=OLLAMA_MODEL,
+        prompt="ask_sum",  # MCP prompt registered from my_mcp_server
+        tools=["add"],  # MCP tool registered from my_mcp_server
+        extract_reasoning=True,
+        )
+```
 
 ## Built-in Events for Tool
 
-{{< hint warning >}}
-**TODO**: How to use the built-in events for tool call request and tool call response, such as ToolRequestEvent and ToolResponseEvent.
-{{< /hint >}}
+Flink Agents provides built-in events for tool call request and tool call response, specifically `ToolRequestEvent` and `ToolResponseEvent`. By default, Flink Agents built-in action will listen to these events and handle the tool call request and tool call response automatically. If you have special needs, you can also define your own action to listen to these events and handle the `ToolRequestEvent` and `ToolResponseEvent` accordingly.
+
+Here is the definition of the `ToolRequestEvent` and `ToolResponseEvent`:
+
+```python
+class ToolRequestEvent(Event):
+    """Event representing a tool call request.
+
+    Attributes:
+    ----------
+    model: str
+        name of the model that generated the tool request.
+    tool_calls : List[Dict[str, Any]]
+        tool calls that should be executed in batch.
+    """
+
+    model: str
+    tool_calls: List[Dict[str, Any]]
+
+  
+class ToolResponseEvent(Event):
+    """Event representing a result from tool call.
+
+    Attributes:
+    ----------
+    request_id : UUID
+        The id of the request event.
+    responses : Dict[UUID, Any]
+        The dict maps tool call id to result.
+    external_ids : Dict[UUID, str]
+        Optional identifier for storing original tool call IDs from external systems
+        (e.g., Anthropic tool_use_id).
+    """
+
+    request_id: UUID
+    responses: Dict[UUID, Any]
+    external_ids: Dict[UUID, str | None]
+```