Observed since 20 Oct, 18:22 UTC
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acp-easy
A dead-simple, LangChain-style client for ACP server.
A lightweight, LangChain-style Python wrapper around the ACP SDK that makes it easy to talk to ACP-compliant agent servers, with auto agent-discovery, sync and async support, and session helpers.
pip install acp-easy
from acp_easy import AcpClient
client = AcpClient(base_url="http://localhost:8000", agent="my-agent")
reply = client.chat(
messages=[
{"role": "user", "content": "Hello!"},
],
model="gpt-4o-mini",
)
print(reply)
Each message can be either:
{"role": ..., "content": ...} dictpartsacp_sdk Message objectIf you don't know what agents your ACP server exposes, list them first:
from acp_easy import AcpClient
client = AcpClient(base_url="http://localhost:8000")
agents = client.list_agents()
print(agents)
# [{'name': 'my-agent', 'description': 'No description provided.'}]
Each entry gives you the name to pass as agent=....
agent at all and the server has exactly one agent, acp-easy auto-resolves it for you.AcpAgentResolutionError listing all available agents so you can pick one.You can set a default agent once at client creation instead of passing it on every call:
client = AcpClient(base_url="http://localhost:8000", agent="my-agent")
Pass any of these keys as the model argument to chat():
| Key | Model |
|---|---|
GLM-5.2 | huggingface/zai-org/GLM-5.2 |
gpt-4o-mini | openai/gpt-4o-mini |
Qwen3-Coder-Next | huggingface/Qwen/Qwen3-Coder-Next |
MiniMAX-M3 | huggingface/MiniMaxAI/MiniMAX-M3 |
DeepSeek-V4-Pro | huggingface/deepseek-ai/DeepSeek-V4-Pro |
acp-easy gives you both sync and async versions of every network call. Use sync in plain scripts, and async inside code that already runs an event loop (FastAPI, Jupyter, asyncio apps).
| Task | Sync | Async |
|---|---|---|
| List agents | client.list_agents() | await client.list_agents_async() |
| Get session | client.get_session(...) | await client.get_session_async(...) |
| Load history | client.load_session_history(...) | await client.load_session_history_async(...) |
| Chat | client.chat(...) | await client.chat_async(...) |
# Inside a FastAPI route / Jupyter notebook / any async function:
agents = await client.list_agents_async()
reply = await client.chat_async(
messages=[{"role": "user", "content": "Hello!"}],
model="gpt-4o-mini",
)
Calling the sync methods (
chat,list_agents) from inside a running event loop will raise a clearRuntimeErrortelling you to use the_asyncversion instead.
acp-easy can work with ACP sessions so historical context can be loaded back from the server, including message parts that point at remote resources with content_url.
Create a local session object and pass it to chat() / chat_async():
from acp_easy import AcpClient
client = AcpClient(base_url="http://localhost:8000", agent="my-agent")
session = client.new_session()
reply = client.chat(
messages=[{"role": "user", "content": "Remember this for later."}],
model="gpt-4o-mini",
session=session,
)
If you already know the session ID, you can fetch it from the server and iterate its history:
session = client.get_session("session-id-from-server")
async for message in client.load_session_history_async(session):
print(message)
Message parts can also reference remote content directly:
reply = client.chat(
messages=[
{
"role": "user",
"parts": [
{
"content_type": "text/plain",
"content_url": "http://resource-server/very-large-text",
}
],
}
],
model="gpt-4o-mini",
)
Pass the full message history as a list if you want to keep the conversation state entirely client-side:
reply = client.chat(
messages=[
{"role": "user", "content": "My name is Ganaik."},
{"role": "assistant", "content": "Nice to meet you, Ganaik!"},
{"role": "user", "content": "What's my name?"},
],
model="gpt-4o-mini",
)
acp-easy raises AcpAgentResolutionError for:
from acp_easy import AcpClient, AcpAgentResolutionError
client = AcpClient(base_url="http://localhost:8000")
try:
reply = client.chat(
messages=[{"role": "user", "content": "Hi"}],
model="gpt-4o-mini",
)
except AcpAgentResolutionError as e:
print(f"Couldn't resolve agent: {e}")
AcpClient(base_url, agent=None, timeout=60.0, session=None)base_url - URL of your ACP server (e.g. "http://localhost:8000")agent - optional default agent name; skips auto-discovery if settimeout - request timeout in seconds (default 60.0)session - optional default ACP session or session ID to reuse across callsclient.list_agents() / await client.list_agents_async()Returns a list of {"name": ..., "description": ...} dicts for all agents on the server.
client.get_session(session_id) / await client.get_session_async(session_id)Fetches the ACP session descriptor from /sessions/{session_id}.
client.load_session_history(session) / await client.load_session_history_async(session)Loads the session's message history and resolves any content_url parts by making HTTP GET requests to their resource servers.
client.chat(messages, model, agent=None, session=None, session_id=None) / await client.chat_async(messages, model, agent=None, session=None, session_id=None)Sends a message history to the resolved agent and returns the agent's text reply.
messages - list of message dicts or acp_sdk Message objectsmodel - model key from the Available models tableagent - optional agent name; overrides the client's default for this call onlysession - optional ACP Session object or session IDsession_id - optional session ID shortcut when you do not already have a session objectDownload counts and popularity will appear here as the collector receives them.
| Package / target | Requirement | Relationship |
|---|---|---|
httpxEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.12",
"evaluation": "NOT_EVALUATED"
} | httpx | runtime |
httpx-sseEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.12",
"evaluation": "NOT_EVALUATED"
} | httpx-sse | runtime |
acp-sdkEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.12",
"evaluation": "NOT_EVALUATED"
} | acp-sdk==1.0.3 | runtime |
uvicornEnvironment{
"extras": "standard",
"marker": null,
"requires_python": ">=3.12",
"evaluation": "NOT_EVALUATED"
} | uvicorn[standard]==0.35.0 | runtime |
bdist_wheel · 6.82 KB · Python py3
sdist · 8.81 KB · Python source
Observed since 20 Oct, 18:22 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package_version:5cdb88ffa3bb1a01a7dd0467185d2c2b2c0defe65b5691fb44c4736a480d2cce