konbakuyomu/smartsearch — explained in plain English
Analysis updated 2026-05-18
Search the web from the terminal with automatic fallback across providers.
Fetch a specific URL as clean readable text for an AI workflow.
Generate a structured, step-by-step deep research plan for a complex question.
| konbakuyomu/smartsearch | anybackup-ai/anybackup | wubing2023/paperspine | |
|---|---|---|---|
| Stars | 221 | 222 | 220 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | hard | moderate |
| Complexity | 2/5 | 4/5 | 3/5 |
| Audience | developer | ops devops | researcher |
Figures from each repo's GitHub metadata at analysis time.
Requires both Python 3.10+ and Node.js installed.
smart-search is a command-line tool that gives AI agents and terminal users a unified, reproducible way to search the web, fetch page content, and plan in-depth research. The problem it solves is that AI tools often need to look things up from live web sources but have no consistent interface for doing so across different search providers, smart-search acts as a single command layer that handles provider routing, fallbacks, and output formatting. You run it from the terminal with commands like searching for a topic, fetching a specific URL as readable text, mapping the structure of a documentation site, or generating a step-by-step "deep research" plan for a complex question. For live searches it routes through multiple providers and automatically falls back to alternatives if the primary fails. The "deep" mode is different, it does not immediately fetch anything, instead it produces a structured research plan with decomposed sub-questions and a list of commands an agent can execute one by one. You would use this if you are building AI workflows that need reliable web research, or if you want a terminal shortcut for fetching clean page content and routing searches across providers. It installs as a global command via npm and requires Python 3.10 or newer alongside Node.js.
A command-line tool giving AI agents and terminal users one consistent interface to search the web, fetch pages, and plan deep research.
Mainly Python. The stack also includes Python, Node.js.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.