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**deepxiv-cli**

AI community intermediate

Description

**DeepXiv is an agent-first paper search and progressive reading tool.**

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

Repository README

This is the README for DeepXiv/deepxiv_sdk, shared by 3 entries in this directory. It describes the repository, not this entry specifically.

deepxiv-sdk

**DeepXiv is an agent-first paper search and progressive reading tool.**

Install it with `pip`, start using it immediately, and let the CLI auto-register an API token on first use. No extra setup is required before your first query.


πŸš€ **Live Demo**: I used vibe coding, based on deepxiv CLI, to build a [DeepResearch demo](https://demo.rag.ac.cn/) in 1 hour β€” feel free to try it out! A full-stack research platform is on the way. Stay tuned.


What DeepXiv Does

DeepXiv is built around two core workflows that matter for agents:

  1. Search + Progressive Content Access
  2. Trending + Popularity signals

Instead of blindly loading full papers, DeepXiv lets agents read in layers, based on token budget and task value.

Quick Start

pip install deepxiv-sdk

On first use, deepxiv automatically registers a free anonymous token (1,000 requests/day) and saves it to `~/.env`:

deepxiv search "agentic memory" --limit 5

If you want the full stack including MCP and the built-in research agent:

pip install "deepxiv-sdk[all]"

CLI-First Workflow

The CLI is the primary interface. DeepXiv is designed so agents can work like researchers: search first, judge quickly, then read only the most valuable parts.

deepxiv search "agentic memory" --limit 5
deepxiv paper 2603.21489 --brief
deepxiv paper 2603.21489 --head
deepxiv paper 2603.21489 --section Analysis

Three commands matter most for progressive reading:

  • --brief: decide whether a paper is worth deeper reading
  • --head: inspect structure, sections, and token distribution
  • --section: read only the most valuable parts such as Introduction, Method, or Experiments

...