Deep Agents ACP integration

This directory contains an Agent Client Protocol (ACP) connector that allows you to run a Python Deep Agent within a text editor that supports ACP such as Zed.

It includes an example coding agent that uses Anthropic's Claude models to write code with its built-in filesystem tools and shell, but you can also connect any Deep Agent with additional tools or different agent architectures!

Getting started

First, make sure you have Zed and uv installed.

Next, clone this repo:

git clone [email protected]:langchain-ai/deepagents.git

Then, navigate into the newly created folder and run uv sync:

cd deepagents/libs/acp
uv sync

Rename the .env.example file to .env and add your Anthropic API key. You may also optionally set up tracing for your Deep Agent using LangSmith by populating the other env vars in the example file:

ini

ANTHROPIC_API_KEY=""

# Set up LangSmith tracing for your Deep Agent (optional)

# LANGSMITH_TRACING=true
# LANGSMITH_API_KEY=""
# LANGSMITH_PROJECT="deepagents-acp"

Finally, add this to your Zed settings.json:

json

{
  "agent_servers": {
    "DeepAgents": {
      "type": "custom",
      "command": "/your/absolute/path/to/deepagents-acp/run_demo_agent.sh"
    }
  }
}

You must also make sure that the run_demo_agent.sh entrypoint file is executable - this should be the case by default, but if you see permissions issues, run:

chmod +x run_demo_agent.sh

Now, open Zed's Agents Panel (e.g. with CMD + Shift + ?). You should see an option to create a new Deep Agent thread:

And that's it! You can now use the Deep Agent in Zed to interact with your project.

If you need to upgrade your version of Deep Agents, run:

uv upgrade deepagents-acp

Launch a custom Deep Agent with ACP

uv add deepagents-acp

python

import asyncio

from acp import run_agent
from deepagents import create_deep_agent
from langgraph.checkpoint.memory import MemorySaver

from deepagents_acp.server import AgentServerACP


async def get_weather(city: str) -> str:
    """Get weather for a given city."""
    return f"It's always sunny in {city}!"


async def main() -> None:
    agent = create_deep_agent(
        tools=[get_weather],
        system_prompt="You are a helpful assistant",
        checkpointer=MemorySaver(),
    )
    server = AgentServerACP(agent)
    await run_agent(server)


if __name__ == "__main__":
    asyncio.run(main())

Launch with Toad

uv tool install -U batrachian-toad --python 3.14

toad acp "python path/to/your_server.py" .
# or
toad acp "uv run python path/to/your_server.py" .