coding-agent-wrapper 0.1.5

Unified Python library and CLI for orchestrating coding agents (Claude Code, Codex, etc.) with MCP tool servers and credential management.

caw

Coding Agent Wrapper — a Python library and CLI for orchestrating coding agents (Claude Code, Codex, opencode) with a unified interface, MCP tool servers, and credential management for Docker containers.

Install

pip install coding-agent-wrapper

Import caw:

import caw

For local development:

pip install -e .

Requires Python 3.10+.

Library: Unified Agent Interface

caw wraps multiple coding agent CLIs behind a single Agent / Session API. Swap providers without changing your code.

Quick start

from caw import Agent

agent = Agent()  # defaults to claude_code
traj = agent.completion("Explain what this repository does")
print(traj.result)
print(f"{traj.usage.total_tokens} tokens, ${traj.usage.cost_usd:.4f}")

Multi-turn sessions

from caw import Agent

agent = Agent(provider="claude_code", model="opus", reasoning="high")
agent.set_system_prompt("You are a security reviewer.")

with agent.start_session() as session:
    turn1 = session.send("Review src/auth.py for vulnerabilities")
    print(turn1.result)

    turn2 = session.send("Now check src/api.py")
    print(turn2.result)

# session.end() called automatically, returns full Trajectory

Resuming sessions across processes

Grab a resume_handle (a string) and store it anywhere — a database, a file, a queue. Later, in a different process, resume the conversation:

# Process 1: start, communicate, persist the handle.
agent = Agent(provider="claude_code")
session = agent.start_session()
session.send("My deploy target is staging-eu. Remember that.")
handle = session.resume_handle          # store this string
session.end()

# Process 2 (later, after a restart): resume by handle.
agent = Agent(provider="claude_code")
session = agent.resume_session(handle)
print(session.send("Where am I deploying?").result)   # -> "staging-eu"
session.end()

The handle is a self-contained JSON string carrying the backend's own resume key, so resuming works even with no data_dir — the underlying CLI still has the conversation:

{"version": 1, "provider": "claude_code", "session_id": "bd260210-…", "resume_key": "bd260210-…"}

(resume_key is claude's session id, Codex's thread_id, or opencode's session id — for codex/opencode it differs from session_id.) Send at least one message before reading resume_handle; the backend assigns its key on the first exchange. Works across all three providers.

The handle grants resume access to the conversation — treat it like a secret, not an opaque random id.

data_dir is optional and additive:

	without data_dir	with the original data_dir
backend conversation	resumed	resumed
caw trajectory	starts empty	full history restored
new turns	not persisted	appended to the original session dir

Providers

Provider	CLI	Provider name
Claude Code	claude	claude_code
Codex	codex	codex
opencode	opencode	opencode

Set via constructor, environment variable, or at runtime:

agent = Agent(provider="codex")
# or
os.environ["CAW_PROVIDER"] = "codex"
# or
agent.set_provider("codex")

MCP tool servers

Attach MCP servers so the agent can call external tools:

from caw import Agent, MCPServer

agent = Agent()
agent.add_mcp_server(MCPServer(
    name="my_db",
    command="python",
    args=["-m", "my_mcp_server"],
))

ToolKit: declarative tool servers

Define tools as Python classes. caw spins up an HTTP MCP server automatically:

from caw import Agent, ToolKit, tool

class UserDB(ToolKit, server_name="user_db"):
    def __init__(self):
        self.users = ["Alice", "Bob"]

    @tool(description="List all users")
    async def list_users(self) -> str:
        return ", ".join(self.users)

    @tool(description="Add a user")
    async def add_user(self, name: str) -> str:
        self.users.append(name)
        return f"Added {name}"

db = UserDB()
agent = Agent(system_prompt="You have access to a user database.")
agent.add_tool_server(db.as_server())

traj = agent.completion("Add Eve to the user database, then list all users")

Subagents

Register child agents that the parent can invoke as tools:

from caw import Agent, AgentSpec

reviewer = AgentSpec(
    name="security_reviewer",
    description="Reviews code for security issues",
    system_prompt="You are a security expert. Review the given code.",
)

agent = Agent()
agent.add_subagent(reviewer)
traj = agent.completion("Review the auth module for vulnerabilities")

# Subagent trajectories are captured:
for sub in traj.subagent_trajectories:
    print(f"  subagent: {sub.agent}, {sub.num_turns} turns")

Data models

Every interaction produces a Trajectory with structured data:

Trajectory
├── agent, model, session_id, created_at
├── turns: list[Turn]
│   ├── input: str
│   ├── output: list[TextBlock | ThinkingBlock | ToolUse]
│   │   └── ToolUse.subagent_trajectory: Trajectory | None
│   ├── usage: UsageStats
│   └── duration_ms: int
├── usage: UsageStats (own)
└── total_usage: UsageStats (own + all nested subagents)

Sessions are persisted to JSONL in caw_data/ by default.

Environment variables

Variable	Purpose
CAW_PROVIDER	Default provider (claude_code, codex)
CAW_MODEL	Default model name
CAW_EFFORT	Default reasoning effort (high, medium, low)

---

CLI: caw auth — Credential Management for Docker Containers

Manages coding agent OAuth credentials so they stay in sync between your host and Docker containers. Supports Claude Code, Codex, and opencode. Host credential files are never modified — they are bind-mounted into the container at run time.

caw auth setup                        # snapshot configs, write mount manifest
caw auth status                       # token expiry, last modified, mount flags
docker run $(caw auth docker-flags) -v ./project:/work my-image
caw auth teardown                     # rm -rf ~/.caw/auth/  (host files untouched)

See caw/auth/README.md for details on how it works, container setup, and supported agents.

License

Apache-2.0