Stream responses in real-time
Get real-time responses from the Agent SDK as text and tool calls stream in
By default, the Agent SDK yields a complete AssistantMessage for each non-empty content block, such as a text block or a tool call, after Claude finishes generating that block. To receive incremental updates as text and tool calls are generated, enable partial message streaming.
Enable streaming output
To enable streaming, set include_partial_messages (Python) or includePartialMessages (TypeScript) to true in your options. This causes the SDK to yield StreamEvent messages containing raw API events as they arrive, in addition to the usual AssistantMessage and ResultMessage.
Your code then needs to:
- Check each message's type to distinguish
StreamEventfrom other message types - For
StreamEvent, extract theeventfield and check itstype - Look for
content_block_deltaevents wheredelta.typeistext_delta, which contain the actual text chunks
The example below enables streaming and prints text chunks as they arrive. Notice the nested type checks: first for StreamEvent, then for content_block_delta, then for text_delta:
from claude_agent_sdk import query, ClaudeAgentOptions
from claude_agent_sdk.types import StreamEvent
import asyncio
async def stream_response():
options = ClaudeAgentOptions(
include_partial_messages=True,
allowed_tools=["Bash", "Read"],
)
async for message in query(prompt="List the files in my project", options=options):
if isinstance(message, StreamEvent):
event = message.event
if event.get("type") == "content_block_delta":
delta = event.get("delta", {})
if delta.get("type") == "text_delta":
print(delta.get("text", ""), end="", flush=True)
asyncio.run(stream_response())
import { query } from "@anthropic-ai/claude-agent-sdk";
for await (const message of query({
prompt: "List the files in my project",
options: {
includePartialMessages: true,
allowedTools: ["Bash", "Read"]
}
})) {
if (message.type === "stream_event") {
const event = message.event;
if (event.type === "content_block_delta") {
if (event.delta.type === "text_delta") {
process.stdout.write(event.delta.text);
}
}
}
}
StreamEvent reference
When partial messages are enabled, you receive raw Claude API streaming events wrapped in an object. The type has different names in each SDK:
- Python:
StreamEvent(import fromclaude_agent_sdk.types) - TypeScript:
SDKPartialAssistantMessagewithtype: 'stream_event'
Both contain raw Claude API events, not accumulated text. You need to extract and accumulate text deltas yourself.
The parent_tool_use_id field is always None in Python and null in TypeScript. Stream events are emitted for the main session only; token-level deltas from subagents aren't forwarded. To attribute output to a subagent, use complete messages, which carry parent_tool_use_id. See Detect subagent invocation.
Claude Code sets user_message_uuid on the turn's first non-ping stream event, and again when the message the turn is answering changes, under the conditions in user_message_uuid. The Python StreamEvent doesn't expose this field.
The event field contains the raw streaming event from the Claude API. Common event types include:
| Event Type | Description |
|---|---|
message_start |
Start of a new message |
content_block_start |
Start of a new content block (text or tool use) |
content_block_delta |
Incremental update to content |
content_block_stop |
End of a content block |
message_delta |
Message-level updates (stop reason, usage) |
message_stop |
End of the message |
Message flow
Claude Code emits an AssistantMessage as each non-empty content block completes, so a response with a text block and a tool call yields two AssistantMessage objects. Each one carries only its own content block, and both share the same message ID, which you read as message.message.id in TypeScript and message.message_id in Python. With partial messages enabled, each AssistantMessage arrives before that block's content_block_stop event, and you receive messages in this order:
StreamEvent (message_start)
StreamEvent (content_block_start) - text block
StreamEvent (content_block_delta) - text chunks...
AssistantMessage - complete text block
StreamEvent (content_block_stop)
StreamEvent (content_block_start) - tool_use block
StreamEvent (content_block_delta) - tool input chunks...
AssistantMessage - complete tool_use block
StreamEvent (content_block_stop)
StreamEvent (message_delta)
StreamEvent (message_stop)
... tool executes ...
... more streaming events for next turn ...
ResultMessage - final result
Without partial messages enabled, you receive all message types except StreamEvent. Common types include SystemMessage (session initialization), AssistantMessage (complete content blocks), ResultMessage (final result), and a compact boundary message indicating when conversation history was compacted (SDKCompactBoundaryMessage in TypeScript; SystemMessage with subtype "compact_boundary" in Python).
Stream tool calls
Tool calls also stream incrementally. You can track when tools start, receive their input as it's generated, and see when they complete. The example below tracks the current tool being called and accumulates the JSON input as it streams in. It uses three event types:
content_block_start: tool beginscontent_block_deltawithinput_json_delta: input chunks arrivecontent_block_stop: tool call complete
from claude_agent_sdk import query, ClaudeAgentOptions
from claude_agent_sdk.types import StreamEvent
import asyncio
async def stream_tool_calls():
options = ClaudeAgentOptions(
include_partial_messages=True,
allowed_tools=["Read", "Bash"],
)
# Track the current tool and accumulate its input JSON
current_tool = None
tool_input = ""
async for message in query(prompt="Read the README.md file", options=options):
if isinstance(message, StreamEvent):
event = message.event
event_type = event.get("type")
if event_type == "content_block_start":
# New tool call is starting
content_block = event.get("content_block", {})
if content_block.get("type") == "tool_use":
current_tool = content_block.get("name")
tool_input = ""
print(f"Starting tool: {current_tool}")
elif event_type == "content_block_delta":
delta = event.get("delta", {})
if delta.get("type") == "input_json_delta":
# Accumulate JSON input as it streams in
chunk = delta.get("partial_json", "")
tool_input += chunk
print(f" Input chunk: {chunk}")
elif event_type == "content_block_stop":
# Tool call complete - show final input
if current_tool:
print(f"Tool {current_tool} called with: {tool_input}")
current_tool = None
asyncio.run(stream_tool_calls())
import { query } from "@anthropic-ai/claude-agent-sdk";
// Track the current tool and accumulate its input JSON
let currentTool: string | null = null;
let toolInput = "";
for await (const message of query({
prompt: "Read the README.md file",
options: {
includePartialMessages: true,
allowedTools: ["Read", "Bash"]
}
})) {
if (message.type === "stream_event") {
const event = message.event;
if (event.type === "content_block_start") {
// New tool call is starting
if (event.content_block.type === "tool_use") {
currentTool = event.content_block.name;
toolInput = "";
console.log(`Starting tool: ${currentTool}`);
}
} else if (event.type === "content_block_delta") {
if (event.delta.type === "input_json_delta") {
// Accumulate JSON input as it streams in
const chunk = event.delta.partial_json;
toolInput += chunk;
console.log(` Input chunk: ${chunk}`);
}
} else if (event.type === "content_block_stop") {
// Tool call complete - show final input
if (currentTool) {
console.log(`Tool ${currentTool} called with: ${toolInput}`);
currentTool = null;
}
}
}
}
Build a streaming UI
This example combines text and tool streaming into a cohesive UI. It tracks whether the agent is currently executing a tool (using an in_tool flag) to show status indicators like [Using Read...] while tools run. Text streams normally when not in a tool, and tool completion triggers a "done" message. This pattern is useful for chat interfaces that need to show progress during multi-step agent tasks.
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage
from claude_agent_sdk.types import StreamEvent
import asyncio
import sys
async def streaming_ui():
options = ClaudeAgentOptions(
include_partial_messages=True,
allowed_tools=["Read", "Bash", "Grep"],
)
# Track whether we're currently in a tool call
in_tool = False
async for message in query(
prompt="Find all TODO comments in the codebase", options=options
):
if isinstance(message, StreamEvent):
event = message.event
event_type = event.get("type")
if event_type == "content_block_start":
content_block = event.get("content_block", {})
if content_block.get("type") == "tool_use":
# Tool call is starting - show status indicator
tool_name = content_block.get("name")
print(f"\n[Using {tool_name}...]", end="", flush=True)
in_tool = True
elif event_type == "content_block_delta":
delta = event.get("delta", {})
# Only stream text when not executing a tool
if delta.get("type") == "text_delta" and not in_tool:
sys.stdout.write(delta.get("text", ""))
sys.stdout.flush()
elif event_type == "content_block_stop":
if in_tool:
# Tool call finished
print(" done", flush=True)
in_tool = False
elif isinstance(message, ResultMessage):
# Agent finished all work
print(f"\n\n--- Complete ---")
asyncio.run(streaming_ui())
import { query } from "@anthropic-ai/claude-agent-sdk";
// Track whether we're currently in a tool call
let inTool = false;
for await (const message of query({
prompt: "Find all TODO comments in the codebase",
options: {
includePartialMessages: true,
allowedTools: ["Read", "Bash", "Grep"]
}
})) {
if (message.type === "stream_event") {
const event = message.event;
if (event.type === "content_block_start") {
if (event.content_block.type === "tool_use") {
// Tool call is starting - show status indicator
process.stdout.write(`\n[Using ${event.content_block.name}...]`);
inTool = true;
}
} else if (event.type === "content_block_delta") {
// Only stream text when not executing a tool
if (event.delta.type === "text_delta" && !inTool) {
process.stdout.write(event.delta.text);
}
} else if (event.type === "content_block_stop") {
if (inTool) {
// Tool call finished
console.log(" done");
inTool = false;
}
}
} else if (message.type === "result") {
// Agent finished all work
console.log("\n\n--- Complete ---");
}
}
Known limitations
- Structured output: with partial messages enabled, the JSON streams as a tool call's unvalidated
input_json_deltachunks, and only the validated result reaches the finalResultMessage.structured_output. See structured outputs for details.
Next steps
Now that you can stream text and tool calls in real-time, explore these related topics:
- Interactive vs one-shot queries: choose between input modes for your use case
- Structured outputs: get typed JSON responses from the agent
- Permissions: control which tools the agent can use