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A dead-simple, LangChain-style client for ACP server.

Project description

acp-easy

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 clear error messages.

Install

pip install acp-easy

Quick start

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 must be a dict with role and content keys, e.g. {"role": "user", "content": "..."}.

Finding your agent name

If 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=....

  • If you don't pass agent at all and the server has exactly one agent, acp-easy auto-resolves it for you.
  • If the server has multiple agents and you don't specify one, you'll get a clear 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")

Available models

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

Sync vs Async

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()
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 clear RuntimeError telling you to use the _async version instead — this avoids the confusing asyncio.run() cannot be called from a running event loop crash.

Multi-turn conversations

Pass the full message history as a list — acp-easy doesn't manage conversation memory for you:

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",
)

Error handling

acp-easy raises AcpAgentResolutionError for:

  • No agents found on the server
  • Multiple agents found with none specified
  • Malformed messages (missing role/content, wrong types)
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}")

API reference

AcpClient(base_url, agent=None, timeout=60.0)

  • base_url — URL of your ACP server (e.g. "http://localhost:8000")
  • agent — optional default agent name; skips auto-discovery if set
  • timeout — request timeout in seconds (default 60.0)

client.list_agents() / await client.list_agents_async()

Returns a list of {"name": ..., "description": ...} dicts for all agents on the server.

client.chat(messages, model, agent=None) / await client.chat_async(messages, model, agent=None)

Sends a message history to the resolved agent and returns the agent's text reply.

  • messages — list of {"role": ..., "content": ...} dicts
  • model — model key from the Available models table
  • agent — optional agent name; overrides the client's default for this call only

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