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Watched how we used GPT-5 and Claude Code with nano-agents here. What? A MCP Server for experimental, small scale engineering agents with multi-provider LLM support. Why?
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agentic-drop-zones
See what you can do with the Agentic Drop Zone in this video. Automated file processing system that monitors directories and triggers agents (Claude Code, Gemini CLI, Codex CLI) when files are dropped.
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Python
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11mo ago
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11mo ago
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Repo: disler/agentic-drop-zones
What's inside
Commands
7/create_imageGenerate image(s) via Replicate/echoEcho the contents of the file at DROPPED_FILE_PATH and provide a brief summary./edit_imageEdit existing images via Replicate using direct curl API calls/finance_categorizerThis command analyzes bank statement CSV files, corrects missing or incorrect categorizations, and generates comprehensive spending reports with visual indicators for high spending areas./more_training_dataAnalyze data patterns and generate additional synthetic training data/morning_debriefTranscribe morning debrief audio and analyze for engineering ideas and priorities
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README
1Agentic Drop Zone
See what you can do with the Agentic Drop Zone in this video.
Automated file processing system that monitors directories and triggers agents (Claude Code, Gemini CLI, Codex CLI) when files are dropped.
Features
- 📝 Simple single file script:
sfs_agentic_drop_zone.py - ⚙️ Configurable drop zones in
drops.yaml - 🤖 Agent agnostic implementation: Claude Code, Gemini CLI, Codex CLI (unimplemented)
- 🧩 Run multiple agents in parallel
- 🚀 Run arbitrary agentic workflows: Do 'anything' your agent can do
System Architecture
graph LR
subgraph "Agentic Drop Zone System"
A[File Dropped] --> B[Watchdog Detects Event]
B --> C{Matches Pattern?}
C -->|Yes| D[Load Prompt Template]
C -->|No| E[Ignore]
D --> F[Replace FILE_PATH Variable]
F --> G{Select Agent}
G -->|claude_code| H[Claude Code<br/>Full tool access<br/>MCP servers]
G -->|gemini_cli| I[Gemini CLI<br/>Google AI<br/>]
G -->|codex_cli| J[Codex CLI<br/>OpenAI<br/>unimplemented]
H --> K[Stream Response]
I --> K
J --> K
K --> L[Display in Console]
L --> B
end
How It Works
- Watch - Monitors configured directories for file events (create/modify/delete/move)
- Match - Checks if dropped files match configured patterns (*.txt, *.json, etc.)
- Process - Executes Claude Code with custom prompts to process the files
- Output - Rich console display with streaming responses in styled panels
Quick Start
# Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Setup environment variables (at least Claude Code API key)
export ANTHROPIC_API_KEY="your-claude-api-key"
export CLAUDE_CODE_PATH="path-to-claude-cli" # default to claude, may need to run which claude to find the path
# Run with uv
uv run sfs_agentic_drop_zone.py
# Drag and drop (copy to reuse) files from example_input_files folder into the drop zone directories
cp example_input_files/echo.txt agentic_drop_zone/echo_zone/
MCP Support
- Claude Code supports MCP servers, run
cp .mcp.json.sample .mcp.jsonand edit the file with your API keys - Gemini CLI supports MCP servers, run
cp .gemini/settings.json.sample .gemini/settings.jsonand edit the file with your API keys - Codex CLI does not support MCP servers without modifying root level
~/.codex/config.toml(untested)
⚠️ Dangerous Agent Execution
IMPORTANT: Agents are given complete control over your system with dangerous execution capabilities. Agent permissions are as follows:
- Claude Code runs with
bypassPermissionsmode, which allows all tools without prompting - Gemini CLI runs with
yoloflag with the--sandboxflag, which auto-approves all actions but prevents moving outside of the sandbox directory - Codex CLI (not implemented)
By using this system, you acknowledge the risks and take full responsibility for any actions performed by the agents.
Configuration (drops.yaml)
drop_zones:
- name: "Image Generation Drop Zone"
file_patterns: ["*.txt", "*.md"] # File types to watch
reusable_prompt: ".claude/commands/create_image.md" # Prompt template
zone_dirs: ["generate_images_zone"] # Directories to monitor
events: ["created"] # Trigger on file creation
agent: "claude_code" # Agent type
model: "sonnet" # Claude model
mcp_server_file: ".mcp.json" # MCP tools config (optional)
create_zone_dir_if_not_exists: true # Auto-create directories
Agents
The system supports multiple AI agents with different capabilities:
Claude Code (Most Capable)
- Status: ✅ Fully implemented
- SDK: Native Python, Typescript, and CLI SDK with streaming support
- Output: Clean, formatted panels with real-time streaming
- Models:
sonnet,opus,haiku - MCP Support: Full MCP tool integration
- Best For: Complex tasks requiring tool use, SOTA performance
- Documentation
Gemini CLI
- Status: 🟡 Implemented with subprocess streaming
- SDK: No SDK - uses CLI via subprocess
- Output: Line-by-line streaming in panels (due to CLI limitations)
- Models:
gemini-2.5-pro(default),gemini-2.5-flash - Flags:
--yolo(auto-approve),--sandbox(sandboxing) - Best For: Quick tasks, alternative models outside of Anthropic models
- Documentation
Codex CLI
- Status: ❌ Not yet implemented
- SDK: Would use CLI via subprocess
- Output: TBD
- Models:
gpt-5 - Best For: Future implementation (Up for a challenge?)
- Documentation
Configuration Example
See drops.yaml for agent setup:
- name: "Claude Zone"
agent: "claude_code"
model: "sonnet"
mcp_server_file: ".mcp.json" # specify this or it won't use MCP tools
- name: "Gemini Zone"
agent: "gemini_cli"
model: "gemini-2.5-pro"
Claude Code SDK Integration
Uses ClaudeSDKClient with streaming responses:
async with ClaudeSDKClient(options=ClaudeCodeOptions(
permission_mode="bypassPermissions",
model="sonnet",
mcp_servers=".mcp.json" # Optional MCP tools
)) as client:
await client.query(prompt)
async for message in client.receive_response():
# Stream responses in Rich panels
Agentic Workflows
The system comes with several pre-configured workflows. Each requires specific setup and environment variables:
🎨 Image Generation Drop Zone
Directory: generate_images_zone/
File Types: *.txt, *.md
Purpose: Generate images from text prompts using Replicate AI models
Requirements:
- Environment variable:
REPLICATE_API_TOKEN(required) - MCP server configuration:
.mcp.json(copy from.mcp.json.sample) - Claude Code with Replicate MCP tools
Usage: Drop a text file containing image prompts. The system will:
- Read each prompt from the file
- Generate images using Replicate's models (default: google/nano-banana)
- Save images with descriptive names and metadata
- Archive the original prompt file
- Open the output directory automatically
🖼️ Image Edit Drop Zone
Directory: edit_images_zone/
File Types: *.txt, *.md, *.json
Purpose: Edit existing images using AI models
Requirements:
- Environment variable:
REPLICATE_API_TOKEN(required) - MCP server configuration:
.mcp.json - Image URLs or paths in the dropped files
Usage: Drop files containing image paths/URLs and editing instructions.
📊 Training Data Generation Zone
Directory: training_data_zone/
File Types: *.csv, *.jsonl (JSON Lines format)
Purpose: Analyze data patterns and generate synthetic training data
Requirements:
- No external API keys required
- Uses Claude Code's built-in analysis capabilities
Usage: Drop data files to:
- Analyze a sample (100 rows) to understand patterns
- Generate 25 additional rows (configurable)
- Append new data using efficient bash commands
- Create extended datasets without loading into memory
- Preserve all original data unchanged
Optimization: Uses bash append operations to handle large files efficiently
🎙️ Morning Debrief Zone
Directory: morning_debrief_zone/
File Types: *.mp3, *.wav, *.m4a, *.flac, *.ogg, *.aac, *.mp4
Purpose: Transcribe morning debrief audio recordings and analyze content for engineering ideas and priorities
Requirements:
- OpenAI Whisper installed:
uv tool install openai-whisper - No API keys required (runs locally)
Usage: Drop audio files to:
- Transcribe using Whisper's tiny model (fast, English)
- Extract top 3 priorities from discussions
- Identify key engineering ideas
- Generate novel extensions and leading questions
- Create structured debrief documents with:
- Date and quarter tracking
- Formatted transcript with bulleted sentences
- Direct commands extracted from transcript
- Archive original audio files after processing
Output: Generates markdown debrief files with comprehensive analysis in morning_debrief_zone/debrief_output/<date_time>/
Improvements
- The
zone_dirsshould be a single directory (zone_dir), and this should be passed into each prompt as a prompt variable (## Variables) and used to create the output directory. Right now it's static in the respective prompts. - Get Codex CLI working (they don't have support for local .codex/config.toml at the time of writing)
- Improve
Gemini CLIstreaming output to be more readable and less line by line based. They don't have an SDK, so we're using the CLI.
Master AI Coding
Learn to code with AI with foundational Principles of AI Coding
Follow the IndyDevDan youtube channel for more Agentic Coding tips and tricks.
File tree
28disler/agentic-drop-zonesView on GitHub
.claude/
commands/
create_image.md
echo.md
edit_image.md
finance_categorizer.md
more_training_data.md
morning_debrief.md
prime.md
.env.sample
.gemini/
settings.json.sample
.gitignore
.mcp.json.sample
ai_docs/
ai_docs.md
astral-uv-single-file-scripts.md
claude-code-python-sdk.md
watch-dog-python-docs.md
drops.yaml
edit_image_input_files/
cat_sitting_in_chair.jpg
example_input_files/
bank_statement.csv
cats_edit.json
cats_enhanced.txt
cats.txt
echo.txt
twitter_classification_dataset.csv
yt_script_5_agent_interaction_patterns_4m.mp4
images/
arch.png
README.md
sfs_agentic_drop_zone.py
specs/
simple_multi_processing_solution.mdMore Flows by @disler.
@dislerFAQ
agentic-drop-zones is a Claude Code plugin with hand-picked skills for automation work, indexed on Flowy. Install it with the command on its page. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
- What is agentic-drop-zones?
- See what you can do with the Agentic Drop Zone in this video. Automated file processing system that monitors directories and triggers agents (Claude Code, Gemini CLI, Codex CLI) when files are dropped.
- How do I install agentic-drop-zones?
- Run these in Claude Code: . Then prompt normally.
- Does agentic-drop-zones auto-invoke its skills?
- Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.
- Is agentic-drop-zones free?
- Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.