Getting Started¶
This guide gets you from a fresh machine to searching, inspecting, and downloading NBER working papers.
Requirements¶
- Python 3.11 or newer.
- Network access to
https://www.nber.org. uv,pipx, orpipfor installation.
The fastest path is uvx, which runs the package in an isolated environment without a permanent install.
Run with uvx¶
uvx nber-cli --version
uvx nber-cli search "Labor Economic"
uvx nber-cli info w25000
uvx nber-cli download w34567
Install as a Tool¶
Use uv tool install when you want the nber-cli command available on your shell path:
You can also install with pipx:
Run as a Python Module¶
The package also exposes a module entry point. This is useful when the nber-cli console script is not on your PATH (for example, when running from a checked-out working tree or inside a virtual environment where the wrapper was not generated):
python -m nber_cli --version
python -m nber_cli search "labor economics"
python -m nber_cli info w25000
python -m nber_cli is functionally identical to the nber-cli command — same arguments, same exit codes, same stdout/stderr contracts. From a working tree you can also run it through uv:
First Search¶
Search accepts title text, author names, abstracts, keywords, and paper numbers. The default result page contains 20 papers.
Add a date range and result size:
Return JSON for scripts:
Read Paper Details¶
Paper IDs can be passed with or without the w prefix:
Use --all to include related fields and published-version information when NBER exposes them:
Follow New Papers with the Feed Cache¶
Initialize the local database:
Fetch the NBER new working papers RSS feed:
The first fetch stores the current RSS items in the cache and displays them as new. Later fetches show only items that were not already cached.
Limit output while showing the latest fetched items:
Clean old cache records:
feed clean asks for confirmation before deleting cached records.
Download a PDF¶
Download into the current directory:
Save into a directory:
Save to an explicit file path:
Batch Download¶
Batch mode supports --save-base; it does not support --file.
Next Steps¶
- Read the CLI Reference for all commands and options.
- Configure the MCP Server for agent workflows.
- Use the Python API in your own async code.