Claude Code ComfyUI Nodes

ComfyUI nodes for integrating Claude Code SDK - enables AI-powered code generation, analysis, and assistance within ComfyUI workflows.

Overview

This node pack provides a stateless, command-based interface to Claude Code within ComfyUI. Unlike traditional chat interfaces, these nodes operate as single-shot commands, making them perfect for automation workflows similar to n8n, Zapier, or Make.

Key Features

• Stateless Command Execution: Each node execution is independent, with explicit memory/context passing
• Folder-Based Output Management: All outputs are organized in timestamped folders
• Context Chaining: Convert previous outputs into memory for subsequent commands
• Argument Substitution: Use variables in commands and memory (e.g., ${PROJECT_NAME})
• Tool Control: Fine-grained control over which tools Claude can use

Nodes

1. Claude Code Command

The main execution node that runs Claude Code commands.

Inputs:

• command: The instruction/command for Claude to execute
• model: Choose between "sonnet" or "opus" models
• max_turns: Maximum iterations Claude can take (1-10)
• memory: Optional context/memory (like CLAUDE.md content)
• arguments: JSON object for variable substitution
• previous_output_folder: Link to previous command's output
• allowed_tools: Comma-separated list of allowed tools

Outputs:

• output_folder: Name of the folder containing all generated files
• claude_response: Claude's final response text
• session_id: Session ID for potential continuations
• execution_metadata: JSON metadata about the execution

2. Claude Code Reader

Inspect and read files from Claude Code output folders.

Inputs:

• output_folder: Folder name from a ClaudeCodeCommand
• file_pattern: Glob pattern for files (e.g., "*.py")
• read_mode: "list_files", "read_all", or "read_specific"
• specific_file: File to read in "read_specific" mode
• max_files: Maximum files to read

Outputs:

• file_contents: The actual file contents
• file_list: JSON list of files with metadata
• metadata: Execution metadata from the folder

3. Claude Code Context Builder

Convert output folders into memory/context for chaining commands.

Inputs:

• output_folder: Folder to build context from
• context_mode: How to build context ("full_content", "file_list", "summary", "custom")
• base_memory: Existing memory to append to
• file_filter: File extensions to include
• custom_template: Custom context template
• max_file_size_kb: Max file size to include

Outputs:

• memory: Formatted memory/context string

Installation

1. Ensure you have ComfyUI installed
2. Clone this repository into your ComfyUI/custom_nodes directory
3. Choose your setup:

Option A: Claude Code Max Plan (Recommended)

If you have a Claude Code Max Plan subscription:

• Install Claude Code from https://claude.ai/code
• The "Claude Code Command (Max Plan)" node will use your existing subscription
• No API key needed, no per-token costs

Option B: Developer API

If you want to use the Anthropic API directly:

• Install dependencies: pip install claude-code-sdk aiofiles
• Set your ANTHROPIC_API_KEY environment variable
• Use the "Claude Code Command (API)" node
• Pay per token based on API usage

4. Restart ComfyUI

Usage Examples

Basic Command Execution

1. Add a "Claude Code Command" node
2. Enter your command, e.g.:

   Create a Python script that generates fibonacci numbers.
   Include error handling and type hints.
   

3. Set model to "sonnet" and max_turns to 3
4. Execute the workflow
5. Check the output folder for generated files

Chaining Commands

1. First command generates code
2. Connect output_folder to a "Claude Code Context Builder"
3. Connect the memory output to a second "Claude Code Command"
4. The second command can reference and build upon the first

Using Arguments

Set arguments as JSON:

{
  "PROJECT_NAME": "MyAwesomeProject",
  "LANGUAGE": "Python"
}

Then use in your command:

Create a ${LANGUAGE} project structure for ${PROJECT_NAME}.
Include README, tests, and proper package structure.

Output Organization

All outputs are stored in claude_code_outputs/ with the structure:

claude_code_outputs/
├── output_20240615_143022_a1b2c3d4/
│   ├── _claude_code_metadata.json
│   ├── generated_script.py
│   └── README.md
└── output_20240615_144512_e5f6g7h8/
    ├── _claude_code_metadata.json
    └── refactored_code.py

Best Practices

1. Be Specific: Clear, detailed commands produce better results
2. Use Context: Chain commands together for complex workflows
3. Manage Tools: Only enable tools that are needed for security
4. Check Outputs: Use the Reader node to verify generated content
5. Template Commands: Save frequently used commands as text files

License

GNU General Public License v3