Connect to A2A protocol agents from Castella. Communicate with agents, display agent cards, send messages, handle responses, and stream results.
A2A (Agent-to-Agent) is an open protocol for AI agent communication and discovery. Castella provides a client for connecting to A2A agents and displaying their information.
When to use: "connect to A2A agent", "A2AClient", "agent card", "send message to agent", "list agent skills", "A2A protocol", "stream agent response"
Connect to an A2A agent:
from castella.a2a import A2AClient
client = A2AClient("http://agent.example.com")
print(f"Connected to: {client.name}")
print(f"Skills: {[s.name for s in client.skills]}")
response = client.ask("What's the weather in Tokyo?")
print(response)
uv sync --extra agent # A2A + A2UI support
The main class for A2A communication:
from castella.a2a import A2AClient
client = A2AClient(
agent_url="http://localhost:8080",
timeout=30.0,
)
| Property | Type | Description |
|----------|------|-------------|
| name | str | Agent name |
| description | str | Agent description |
| version | str | Agent version |
| skills | list[AgentSkill] | Available skills |
| is_connected | bool | Connection status |
| supports_streaming | bool | Streaming capability |
| agent_card | AgentCard | Full agent metadata |
# Synchronous ask
response = client.ask("Hello!")
# Asynchronous ask
response = await client.ask_async("Hello!")
# Streaming (async)
async for chunk in client.ask_stream("Tell me a story"):
print(chunk, end="", flush=True)
# Send structured message
from castella.a2a import Message
response = client.send_message(Message(role="user", content="Hello"))
# Check skills
if client.has_skill("get_weather"):
skill = client.get_skill("get_weather")
print(f"Skill: {skill.name} - {skill.description}")
Access agent metadata via the agent card:
from castella.a2a import A2AClient
client = A2AClient("http://agent.example.com")
card = client.agent_card
print(f"Name: {card.name}")
print(f"Description: {card.description}")
print(f"Version: {card.version}")
print(f"URL: {card.url}")
# List skills
for skill in card.skills:
print(f" - {skill.name}: {skill.description}")
print(f" Tags: {skill.tags}")
Skills define agent capabilities:
skill = client.get_skill("get_weather")
print(skill.name) # "get_weather"
print(skill.description) # "Get current weather"
print(skill.tags) # ["weather", "api"]
print(skill.examples) # ["What's the weather in Tokyo?"]
from castella.a2a import A2AClient, A2AConnectionError, A2AResponseError
try:
client = A2AClient("http://agent.example.com")
response = client.ask("Hello")
except A2AConnectionError as e:
print(f"Connection failed: {e}")
except A2AResponseError as e:
print(f"Agent error: {e}")
For long-running responses:
async def stream_story():
client = A2AClient("http://agent.example.com")
if client.supports_streaming:
async for chunk in client.ask_stream("Tell me a story"):
print(chunk, end="", flush=True)
else:
# Fallback to non-streaming
response = await client.ask_async("Tell me a story")
print(response)
Display agent card in Castella UI:
from castella import App, Column
from castella.agent import AgentCardView
from castella.a2a import A2AClient
from castella.frame import Frame
client = A2AClient("http://agent.example.com")
card_view = AgentCardView(
client.agent_card,
show_skills=True,
compact=False,
)
App(Frame("Agent Info", 400, 300), card_view).run()
Use A2AClient with high-level chat components:
from castella.agent import AgentChat
# Automatic connection and chat UI
chat = AgentChat.from_a2a("http://localhost:8080")
chat.run()
See the castella-agent-ui skill for more chat options.
For creating A2A servers, use python-a2a directly:
from python_a2a import A2AServer, skill, run_server
class WeatherAgent(A2AServer):
@skill(name="get_weather", description="Get current weather")
def get_weather(self, location: str) -> str:
return f"Weather in {location}: Sunny, 22°C"
agent = WeatherAgent(
name="Weather Agent",
description="Provides weather information",
version="1.0.0",
url="http://localhost:8080",
)
run_server(agent, port=8080)
Check capabilities before using features:
if client.supports_streaming:
async for chunk in client.ask_stream(msg):
...
Handle errors gracefully:
try:
response = client.ask(msg)
except A2AConnectionError:
# Retry or show offline message
Use async for UI responsiveness:
response = await client.ask_async(msg)
Inspect skills for routing:
if client.has_skill("search"):
# Route search queries to this agent
references/types.md - AgentCard, AgentSkill, Message typesreferences/streaming.md - Streaming response handlingscripts/ - Executable examples (a2a_connect.py, a2a_async.py)Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Start voice calls via the OpenClaw voice-call plugin.
Notion API for creating and managing pages, databases, and blocks.
Gemini CLI for one-shot Q&A, summaries, and generation.
Category:developer