diff --git a/content/docs/SDKs/python/agent-to-agent.mdx b/content/docs/SDKs/python/agent-to-agent.mdx
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+---
+title: Agent-to-Agent Communication
+description: Enable communication between agents in the Agentuity Python SDK
+---
+
+# Agent-to-Agent Communication
+
+The Agentuity Python SDK enables seamless communication between agents, whether they are running locally or in different environments.
+
+## Local Agent Communication
+
+You can easily communicate between agents running in the same process:
+
+```python
+async def run(request, response, context):
+    # Call another agent by ID
+    return await response.handoff({"id": "other_agent_id"})
+    
+    # Or call by name
+    # return response.handoff({"name": "OtherAgentName"})
+```
+
+## Remote Agent Communication
+
+The SDK now supports communication with agents running in different environments:
+
+```python
+async def run(request, response, context):
+    # Resolve an agent (local or remote)
+    agent = context.get_agent({"id": "remote_agent_id"})
+    
+    # Create data for the remote agent
+    from agentuity.server.data import Data, StringStreamReader
+    data = Data("text/plain", StringStreamReader("Hello from another agent"))
+    
+    # Call the remote agent
+    result = await agent.run(data, metadata={"key": "value"})
+    
+    # Process the response
+    text = await result.data.text()
+    return response.text(f"Got response: {text}")
+```
+
+## Agent Resolution
+
+The `AgentContext` provides methods for resolving agents, whether they are local or remote:
+
+```python
+async def run(request, response, context):
+    # Resolve by ID
+    agent = context.get_agent({"id": "agent_id"})
+    
+    # Resolve by name
+    agent = context.get_agent({"name": "AgentName"})
+    
+    # Resolve by name in a specific project
+    agent = context.get_agent({"name": "AgentName", "projectId": "proj_123"})
+    
+    # Call the resolved agent
+    result = await agent.run(request.data)
+    return result
+```
+
+## Agent Context
+
+The `AgentContext` class provides methods for agent resolution and management:
+
+```python
+async def run(request, response, context):
+    # Get agent information
+    current_agent = context.agent
+    all_agents = context.agents
+    
+    # Get the current scope (local or remote)
+    scope = context.scope
+    
+    # Get the current run ID
+    run_id = context.runId
+    
+    # Use key-value store
+    await context.kv.set("key", "value")
+    value = await context.kv.get("key")
+    
+    # Use vector store
+    await context.vector.add("collection", "id", [0.1, 0.2, 0.3], {"metadata": "value"})
+    results = await context.vector.search("collection", [0.1, 0.2, 0.3], 5)
+    
+    return response.text("Agent context example")
+```
diff --git a/content/docs/SDKs/python/async-api.mdx b/content/docs/SDKs/python/async-api.mdx
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+---
+title: Async API
+description: Working with Asynchronous Agents in the Agentuity Python SDK
+---
+
+# Async API
+
+The Agentuity Python SDK now supports fully asynchronous operations, enabling more efficient handling of concurrent requests and streaming responses.
+
+## Agent Request
+
+The `AgentRequest` class now uses async patterns to handle incoming data:
+
+```python
+from agentuity.server import AgentRequest
+
+async def run(request: AgentRequest, response, context):
+    # Access request data asynchronously
+    data = await request.data.text()
+    
+    # Access request metadata
+    metadata = request.metadata
+    
+    # Get the trigger type
+    trigger = request.trigger
+    
+    # Return a response
+    return response.text(f"Received: {data}")
+```
+
+## Agent Response
+
+The `AgentResponse` class supports async streaming and iteration:
+
+```python
+from agentuity.server import AgentResponse
+
+async def run(request, response: AgentResponse, context):
+    # Stream response data
+    async def data_generator():
+        for i in range(5):
+            yield f"Data chunk {i}\n"
+    
+    # Return a streaming response
+    return response.stream(data_generator(), contentType="text/plain")
+```
+
+### Async Iteration
+
+Responses can be iterated over asynchronously:
+
+```python
+async def process_response(response):
+    async for chunk in response:
+        print(chunk)
+```
+
+## Data Streaming
+
+The SDK provides several specialized stream readers for different data types:
+
+```python
+from agentuity.server.data import (
+    StringStreamReader,
+    BytesStreamReader,
+    EmptyDataReader
+)
+
+# Create a stream from a string
+string_stream = StringStreamReader("Hello, world!")
+
+# Create a stream from bytes
+bytes_stream = BytesStreamReader(b"Binary data")
+
+# Create an empty stream
+empty_stream = EmptyDataReader()
+```
+
+## Performance Benefits
+
+The async implementation provides several advantages:
+
+- Efficient handling of concurrent requests
+- Streaming of large data payloads without blocking
+- Reduced memory usage for processing large files
+- Better integration with modern async Python applications
diff --git a/content/docs/SDKs/python/data-handling.mdx b/content/docs/SDKs/python/data-handling.mdx
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+---
+title: Data Handling
+description: Working with various data types in the Agentuity Python SDK
+---
+
+# Data Handling
+
+The Agentuity Python SDK provides a flexible system for working with different types of data, from text and JSON to binary formats like images and audio.
+
+## The Data Class
+
+The `Data` class serves as a container for all types of content:
+
+```python
+from agentuity.server.data import Data, StringStreamReader, BytesStreamReader
+
+# Create a text Data object
+text_data = Data("text/plain", StringStreamReader("Hello, world!"))
+
+# Create a binary Data object
+binary_data = Data("application/octet-stream", BytesStreamReader(b"\x00\x01\x02\x03"))
+```
+
+## Accessing Data Content
+
+Data content can be accessed in various formats:
+
+```python
+async def process_data(data: Data):
+    # Get as text
+    text = await data.text()
+    
+    # Get as JSON
+    json_data = await data.json()
+    
+    # Get as binary
+    binary = await data.binary()
+    
+    # Get as base64 encoded string
+    base64_str = await data.base64()
+    
+    # Access as a stream
+    stream = await data.stream()
+    async for chunk in stream:
+        process_chunk(chunk)
+```
+
+## Working with Responses
+
+The `AgentResponse` class provides methods for various content types:
+
+```python
+async def run(request, response, context):
+    # Text response
+    return response.text("Hello, world!")
+    
+    # JSON response
+    return response.json({"message": "Hello, world!"})
+    
+    # Markdown response
+    return response.markdown("# Hello, world!")
+    
+    # Binary response
+    return response.binary(b"\x00\x01\x02\x03", "application/octet-stream")
+```
+
+## Media Type Helpers
+
+The SDK includes helpers for common media types:
+
+```python
+async def run(request, response, context):
+    # Image responses
+    with open("image.png", "rb") as f:
+        image_data = f.read()
+        return response.png(image_data)
+    
+    # Other image formats
+    return response.jpeg(jpeg_data)
+    return response.gif(gif_data)
+    return response.webp(webp_data)
+    
+    # Document formats
+    return response.pdf(pdf_data)
+    
+    # Audio/Video formats
+    return response.mp3(mp3_data)
+    return response.mp4(mp4_data)
+    return response.wav(wav_data)
+    return response.ogg(ogg_data)
+    return response.webm(webm_data)
+    return response.m4a(m4a_data)
+```
+
+## Streaming Data
+
+For large responses or real-time data, use streaming:
+
+```python
+async def run(request, response, context):
+    # Stream data from a generator
+    async def generator():
+        for i in range(10):
+            yield f"Item {i}\n"
+    
+    # Return the stream
+    return response.stream(generator(), contentType="text/plain")
+    
+    # Transform items during streaming
+    def transform(item):
+        return f"Transformed: {item}"
+    
+    return response.stream(generator(), transform=transform)
+    
+    # Stream responses from another agent
+    other_response = await context.get_agent("other_agent").run(request.data)
+    return response.stream(other_response)
+```
diff --git a/content/docs/SDKs/python/index.mdx b/content/docs/SDKs/python/index.mdx
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+---
+title: Python SDK
+description: Agentuity Python SDK Documentation
+---
+
+# Agentuity Python SDK
+
+The Agentuity Python SDK is a powerful toolkit for building, deploying, and managing AI agents in Python environments. This SDK provides developers with a comprehensive set of tools to create intelligent agents that can process various types of content, communicate with each other, and integrate with external systems.
+
+## Prerequisites
+
+- [Python](https://www.python.org/) (3.10 or 3.11)
+- [uv](https://docs.astral.sh/uv/) (latest version recommended)
+
+## Installation
+
+First, install the Agentuity CLI:
+
+```bash
+curl -sSL https://agentuity.sh/install.sh | bash
+```
+
+Then create a new project:
+
+```bash
+agentuity new
+```
+
+This will create a new project with a default `agentuity.yaml` configuration file and agent structure.
+
+## Creating Your First Agent
+
+Navigate to the agent file created by the CLI:
+
+```bash
+cd agents/myfirstagent
+```
+
+Edit the `agent.py` file and add the following code:
+
+```python
+from agentuity.server import AgentRequest, AgentResponse, AgentContext
+
+def run(request: AgentRequest, response: AgentResponse, context: AgentContext):
+    return response.text("Hello, world")
+```
+
+## Running Your Agent
+
+Start the local development server:
+
+```bash
+agentuity dev
+```
+
+When the server starts, you'll see a local URL in the console output. Open this URL in your browser to access the Agentuity development UI, where you can test your agent and view the responses.
+
+## Key Features
+
+<div style={{ display: 'grid', gridTemplateColumns: 'repeat(auto-fit, minmax(250px, 1fr))', gap: '1rem', padding: '1rem' }}>
+  <Card href="/docs/SDKs/python/async-api">
+    <h3>Async API</h3>
+    <p>Work with fully asynchronous agents</p>
+  </Card>
+  
+  <Card href="/docs/SDKs/python/agent-to-agent">
+    <h3>Agent-to-Agent Communication</h3>
+    <p>Enable communication between local and remote agents</p>
+  </Card>
+  
+  <Card href="/docs/SDKs/python/data-handling">
+    <h3>Data Handling</h3>
+    <p>Work with various data types and streaming capabilities</p>
+  </Card>
+</div>