llm-claude-cli 0.1.0

LLM plugin for Claude models via Claude Code CLI

llm-claude-cli

LLM plugin for using Claude models through the Claude Code CLI.

This plugin allows you to use Claude models via the claude command-line tool, leveraging your existing Claude Code subscription without requiring a separate API key.

Installation

First, ensure you have Claude Code CLI installed and authenticated:

npm install -g @anthropic-ai/claude-code
claude auth login

Then install this plugin:

llm install llm-claude-cli

Or install from source:

pip install -e .

Usage

Basic usage

# Use the default Claude CLI model
llm -m claude-cli "What is the capital of France?"

# Use specific model variants
llm -m claude-cli-opus "Explain quantum computing"
llm -m claude-cli-sonnet "Write a haiku about programming"
llm -m claude-cli-haiku "Quick summary of Python decorators"

Available models

Model ID	Aliases	Description
claude-cli	ccli	Default Claude CLI model
claude-cli-opus	ccli-opus	Claude Opus 4.5
claude-cli-sonnet	ccli-sonnet	Claude Sonnet 4.5
claude-cli-haiku	ccli-haiku	Claude Haiku 4.5

Using aliases

llm -m ccli "Hello, Claude!"
llm -m ccli-opus "Deep analysis of this code"
llm -m ccli-sonnet "Explain this concept"
llm -m ccli-haiku "Quick answer"

Options

# Set maximum tokens
llm -m claude-cli "Summarize this" -o max_tokens 500

# Set timeout (in seconds, default 300)
llm -m claude-cli "Complex task" -o timeout 600

# Limit allowed tools
llm -m claude-cli "Read file.txt" -o allowedTools "Read,Glob"

# Block specific tools
llm -m claude-cli "Help me code" -o disallowedTools "Bash(rm:*),Bash(sudo:*)"

# Set max turns for agentic operations
llm -m claude-cli "Build a web app" -o max_turns 10

# Add additional directories for Claude to access
llm -m claude-cli "Review the frontend" -o add_dir '["../frontend", "../shared"]'

# Set working directory
llm -m claude-cli "Run the tests" -o cwd "/path/to/project"

# Set permission mode (default, acceptEdits, bypassPermissions)
llm -m claude-cli "Refactor this" -o permission_mode "acceptEdits"

# Manually resume a specific Claude Code session (for advanced use)
llm -m claude-cli "Continue from where we left off" -o resume "session-id-here"

# Use custom MCP configuration
llm -m claude-cli "Use my tools" -o mcp_config "/path/to/mcp.json"

# Enable verbose logging
llm -m claude-cli "Debug this" -o verbose true

System Prompts

You can customize the system prompt in two ways:

# Append to Claude Code's default system prompt (recommended)
# This preserves Claude Code's agentic capabilities while adding your instructions
llm -m claude-cli "Analyze this code" -o system_prompt "Focus on security vulnerabilities"

# Fully replace the default system prompt
# Use this when you want complete control over Claude's behavior
llm -m claude-cli "Hello" -o system_prompt "You are a pirate" -o replace_system_prompt true

# Using LLM's built-in --system flag (appends by default)
llm -m claude-cli "Review this PR" --system "You are a senior code reviewer"

The default behavior appends to Claude Code's system prompt using --append-system-prompt, which preserves agentic tool use. Set replace_system_prompt to true to fully override with --system-prompt.

Streaming

Streaming is enabled by default. The plugin uses Claude Code's stream-json output format for real-time token streaming.

# Streaming output (default)
llm -m claude-cli "Tell me a story"

# Disable streaming
llm -m claude-cli "Quick answer" --no-stream

Schemas (Structured Output)

This plugin supports LLM's schema feature for structured JSON output. Use the --schema flag to specify the expected output format:

# Simple schema with field types
llm -m claude-cli "Invent a cool dog" --schema 'name, age int, breed'

# Complex schema
llm -m claude-cli "List 3 countries" --schema '
  countries: [{
    name,
    capital,
    population int
  }]
'

# Using a JSON schema file
llm -m claude-cli "Extract info" --schema-file schema.json

The plugin uses Claude Code's --json-schema flag to ensure structured output conformance.

Python API

import llm

# Get a model
model = llm.get_model("claude-cli")

# Basic prompt
response = model.prompt("What is Python?")
print(response.text())

# With system prompt
response = model.prompt("Explain decorators", system="You are a Python expert")
print(response.text())

# Streaming
for chunk in model.prompt("Tell me a story", stream=True):
    print(chunk, end="", flush=True)

# Conversation
conversation = model.conversation()
response1 = conversation.prompt("My name is Alice")
response2 = conversation.prompt("What's my name?")
print(response2.text())  # Should mention Alice

# Schema for structured output
import json

schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "age": {"type": "integer"},
        "breed": {"type": "string"}
    },
    "required": ["name", "age", "breed"]
}

response = model.prompt("Invent a cool dog", schema=schema)
dog = json.loads(response.text())
print(f"Name: {dog['name']}, Age: {dog['age']}, Breed: {dog['breed']}")

How it works

This plugin invokes the Claude Code CLI (claude) as a subprocess with the -p flag for non-interactive prompts. It supports:

• Streaming: Uses --output-format stream-json for real-time NDJSON streaming
• Non-streaming: Uses --output-format json for complete responses
• Schemas: Uses --json-schema for structured JSON output conformance
• System prompts: Uses --append-system-prompt (default) or --system-prompt (replace)
• Conversations: Captures Claude Code session IDs and auto-resumes via --resume for multi-turn conversations
• Model selection: Passes --model flag to select Opus, Sonnet, or Haiku
• Directory access: Uses --add-dir for multi-directory projects
• Permission control: Uses --permission-mode and tool filtering
• MCP integration: Uses --mcp-config for custom tool servers

Requirements

• Python 3.10+
• LLM 0.26+
• Claude Code CLI installed and authenticated

License

MIT License - see LICENSE for details.