yulinlina

agent-receipts

Community yulinlina
Updated

Append-only local receipts for AI agent actions: capture commands, outputs, and handoff evidence, then expose them to agents over MCP.

agent-receipts

Append-only local receipts for AI agent actions: capture commands, outputs, and handoff evidence, then expose them to agents over MCP.

License Language Status PyPI Tests

๐ŸŽฏ Why?

Trending agent projects increasingly mention evidence logs, verifiable handoffs, and agent observability, but most solutions are large frameworks or platform-specific hubs. Developers using Claude Code, Codex, OpenCode, or custom agents need a tiny local-first tool that simply records what happened and proves it was not edited. agent-receipts fills that gap with a zero-depend CLI plus a minimal MCP adapter.

Target audience: Developers running AI coding agents, agent-framework authors, and platform/security engineers who need lightweight local audit trails, reproducible handoffs, and evidence that an agent really ran a command or completed a step.

โœจ Features

  • โœจ Capture command executions with stdout/stderr tails, exit codes, duration, cwd, agent, session, and tags
  • โœจ Append-only hash-chained JSONL receipts with tamper detection via verify
  • โœจ Manual evidence notes for handoffs, plus search/export and a minimal MCP stdio server

๐Ÿš€ Quick Start

# Install
pip install agent-receipts

# Run
agent-receipts --help

๐Ÿ“ฆ Installation

From Source

git clone https://github.com/YOUR_USERNAME/agent-receipts.git
cd agent-receipts
# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest -v

๐ŸŽฌ Demo

The GIF above was recorded using Charm VHS:

vhs < demo.tape

๐Ÿ“– Usage

# Show help
agent-receipts --help

# Common usage examples
agent-receipts --example

๐Ÿ—๏ธ Architecture

graph LR
    A[Input] --> B[Core Engine]
    B --> C[Output]
    B --> D[Plugins]
    D --> E[Extensions]

๐Ÿค Contributing

Contributions are welcome! Please:

  1. Fork the repo
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

๐Ÿ“„ License

MIT ยฉ 2026 โ€” See LICENSE for details.

If this project helped you, please โญ star it!

Made with โค๏ธ and AI

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