opencode-agent-sdk 0.2.0

Open-source Agent SDK backed by OpenCode ACP (drop-in replacement for claude_agent_sdk)

OpenCode Agent SDK for Python

Python SDK for building agents backed by OpenCode. Drop-in replacement for claude_agent_sdk with support for any LLM provider (Anthropic, OpenAI, xAI, etc.).

Installation

pip install opencode-agent-sdk

Prerequisites:

• Python 3.10+
• An OpenCode server (opencode serve) or the opencode CLI installed locally

Quick Start

import asyncio
from opencode_agent_sdk import SDKClient, AgentOptions, AssistantMessage, TextBlock

async def main():
    client = SDKClient(options=AgentOptions(
        model="claude-haiku-4-5",
        server_url="http://localhost:54321",
    ))

    await client.connect()
    await client.query("What is 2 + 2?")

    async for message in client.receive_response():
        if isinstance(message, AssistantMessage):
            for block in message.content:
                if isinstance(block, TextBlock):
                    print(block.text)

    await client.disconnect()

asyncio.run(main())

SDKClient

SDKClient supports bidirectional conversations with an LLM via OpenCode. It works in two transport modes:

• HTTP mode — communicates with a running opencode serve instance over REST
• Subprocess mode — spawns opencode acp locally over stdio JSON-RPC

HTTP Mode (recommended)

Start the server, then connect:

docker compose up -d   # starts opencode serve on port 54321

from opencode_agent_sdk import SDKClient, AgentOptions

client = SDKClient(options=AgentOptions(
    model="claude-haiku-4-5",
    server_url="http://localhost:54321",
    system_prompt="You are a helpful assistant",
))

await client.connect()
await client.query("Hello!")

async for msg in client.receive_response():
    print(msg)

await client.disconnect()

Subprocess Mode

When server_url is not set, the SDK spawns opencode acp as a child process:

client = SDKClient(options=AgentOptions(
    cwd="/path/to/project",
    model="claude-haiku-4-5",
))

Resuming Sessions

options = AgentOptions(
    resume="session-id-from-previous-run",
    server_url="http://localhost:54321",
)

AgentOptions

Field	Type	Default	Description
cwd	str	"."	Working directory
model	str	""	Model identifier (e.g. "claude-haiku-4-5")
provider_id	str	"anthropic"	Provider identifier
system_prompt	str	""	System prompt for the LLM
server_url	str	""	OpenCode server URL; enables HTTP mode when set
mcp_servers	dict	{}	MCP server configurations
allowed_tools	list[str]	[]	Tools the agent is allowed to use
permission_mode	str	""	Permission mode for tool execution
hooks	dict	{}	Hook matchers keyed by event type
max_turns	int	100	Maximum conversation turns
resume	str | None	None	Session ID to resume

Custom Tools (MCP Servers)

Define tools as Python functions and expose them as in-process MCP servers:

from opencode_agent_sdk import tool, create_sdk_mcp_server, SDKClient, AgentOptions

@tool("greet", "Greet a user", {"type": "object", "properties": {"name": {"type": "string"}}})
def greet_user(args):
    return {"content": [{"type": "text", "text": f"Hello, {args['name']}!"}]}

server = create_sdk_mcp_server("my-tools", tools=[greet_user])

client = SDKClient(options=AgentOptions(
    mcp_servers={"my-tools": server},
    allowed_tools=["mcp__my-tools__greet"],
    server_url="http://localhost:54321",
))

You can mix in-process SDK servers with external MCP servers:

options = AgentOptions(
    mcp_servers={
        "internal": sdk_server,          # In-process SDK server
        "external": {                    # External stdio server
            "command": "external-server",
            "args": ["--port", "8080"],
        },
    }
)

Hooks

Hooks let you intercept and control tool execution. They run deterministically at specific points in the agent loop.

from opencode_agent_sdk import SDKClient, AgentOptions, HookMatcher

async def check_bash_command(input_data, tool_use_id, context):
    tool_input = input_data["tool_input"]
    command = tool_input.get("command", "")

    if "rm -rf" in command:
        return {
            "hookSpecificOutput": {
                "hookEventName": "PreToolUse",
                "permissionDecision": "deny",
                "permissionDecisionReason": "Destructive command blocked",
            }
        }
    return {}

options = AgentOptions(
    allowed_tools=["Bash"],
    hooks={
        "PreToolUse": [
            HookMatcher(matcher="Bash", hooks=[check_bash_command]),
        ],
    },
    server_url="http://localhost:54321",
)

client = SDKClient(options=options)
await client.connect()
await client.query("Run: echo hello")

async for msg in client.receive_response():
    print(msg)

await client.disconnect()

Hook event types: "PreToolUse", "Stop"

Types

See src/opencode_agent_sdk/types.py for complete type definitions:

• AssistantMessage — LLM response containing TextBlock and/or ToolUseBlock
• ResultMessage — Final message with usage stats, cost, and session info
• SystemMessage — Internal events (init, tool results, thoughts)
• TextBlock — Text content from the LLM
• ToolUseBlock — Tool invocation with name and input
• HookMatcher — Matches tool names to hook functions

Error Handling

from opencode_agent_sdk._errors import ProcessError

try:
    await client.connect()
except ProcessError as e:
    print(f"Failed with exit code: {e.exit_code}")

Migrating from claude_agent_sdk

This SDK mirrors the claude_agent_sdk API. Migration requires renaming imports:

# Before (claude_agent_sdk)
from claude_agent_sdk import (
    ClaudeAgentOptions, ClaudeSDKClient, AssistantMessage,
    ResultMessage, SystemMessage, TextBlock, ToolUseBlock, HookMatcher,
)
from claude_agent_sdk._errors import ProcessError

# After (opencode_agent_sdk)
from opencode_agent_sdk import (
    AgentOptions, SDKClient, AssistantMessage,
    ResultMessage, SystemMessage, TextBlock, ToolUseBlock, HookMatcher,
)
from opencode_agent_sdk._errors import ProcessError

All method calls, message types, hooks, and tool decorators stay the same. Only the class names change:

claude_agent_sdk	opencode_agent_sdk
ClaudeSDKClient	SDKClient
ClaudeAgentOptions	AgentOptions

Demo: End-to-End Walkthrough

A full working demo that connects to opencode serve, sends a prompt to clone a GitHub repo, and streams the LLM response back through the SDK.

1. Configure API keys

Create a .env file in the project root with your provider key:

ANTHROPIC_API_KEY=sk-ant-...

2. Start the server

docker compose up -d opencode

This builds and starts the opencode serve container on port 54321.

3. Install dependencies

uv sync

4. Run the E2E demo

uv run python scripts/e2e_test.py

Expected output

============================================================
E2E Test: Clone repo & explain project
============================================================
Server: http://127.0.0.1:54321

[*] Connecting ...
[*] Connected.

[>] Prompt:
Clone the repo https://github.com/dingkwang/opencode-agent-sdk-python and then
explain what the project does. Give a concise summary of its purpose,
architecture, and key components.

------------------------------------------------------------

  [system:init]
  [system:step_start]

  [assistant]
  ## opencode-agent-sdk-python
  ### Purpose
  An open-source Python SDK that serves as a drop-in replacement for Anthropic's
  proprietary `claude_agent_sdk`. It delegates all LLM work to OpenCode — an
  open-source headless server that supports any provider ...
  ...

============================================================
  [result] session  = ses_...
           cost     = $0.024723
           turns    = 1
           is_error = False
============================================================

[*] Message counts: {'system': 2, 'assistant': 1, 'result': 1}
[*] E2E test complete.

What's happening

1. SDKClient creates an HTTP session against opencode serve
2. query() sends the user prompt via POST /session/{id}/message
3. receive_response() yields typed messages: SystemMessage (init, step events), AssistantMessage (LLM text/tool calls), and ResultMessage (cost, session ID, turn count)
4. disconnect() cleans up the session

Customizing the demo

Set a custom server URL via environment variable:

OPENCODE_SERVER_URL=http://your-host:54321 uv run python scripts/e2e_test.py

Running with Docker

# Start opencode serve
docker compose up -d

# Run the integration test
docker compose run --rm test

The Docker setup uses opencode-ai v1.2.6 and exposes the REST API on port 54321. Pass provider API keys via .env (e.g. ANTHROPIC_API_KEY).

Development

# Install dependencies
uv sync

# Run tests
uv run pytest

# Run demo against a running opencode serve
uv run python scripts/opencode_ai_demo.py

# Interactive multi-turn chat
uv run python scripts/chat.py

License

MIT