Quickstart

ACP Kit has two primary adapter entry paths:

• pydantic-acp for pydantic_ai.Agent
• langchain-acp for LangChain, LangGraph, and DeepAgents graphs

The repo also ships helper packages around those adapters:

• acpremote for existing ACP agents and stdio ACP commands
• codex-auth-helper for Codex-backed Pydantic AI or LangChain model construction

Those helper packages do not replace the adapters. They sit around them:

• acpremote moves ACP boundaries across WebSocket transport
• codex-auth-helper builds a Codex-backed Responses model for pydantic-ai or a Codex-backed ChatOpenAI for LangChain

Choose the path that matches the runtime you already have.

Pydantic AI Path

Use this when your integration starts from a normal pydantic_ai.Agent.

• Pydantic Quickstart
• Pydantic ACP Overview
• Finance Agent example

LangChain And LangGraph Path

Use this when your integration starts from:

• langchain.agents.create_agent(...)
• a compiled LangGraph graph

• a DeepAgents graph built with create_deep_agent(...)

• LangChain Quickstart

• LangChain ACP Overview
• Codex-backed LangChain example
• LangChain Workspace Graph example
• DeepAgents Compatibility Example

Shared Next Steps

After the adapter-specific quickstart, the next useful ACP Kit seams are usually:

• acpremote Overview if you need to expose an existing ACP server remotely
• Helpers for the helper package map
• CLI for acpkit run ... and acpkit launch ...
• Pydantic Providers if you are integrating pydantic-acp
• Pydantic Bridges if you are integrating pydantic-acp
• Pydantic Host Backends and Projections for pydantic-acp
• LangChain Providers if you are integrating langchain-acp
• LangChain Bridges if you are integrating langchain-acp
• LangChain Projections and Event Projection Maps for langchain-acp