alpha-hub/README.md
Advait Paliwal 9a708a1ab9 Alpha Hub: Context Hub for research papers
CLI + MCP server for searching papers and building persistent knowledge.
Powered by alphaXiv for semantic search, paper reports, and PDF Q&A.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-18 19:55:44 -07:00

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# Alpha Hub
Research agents hallucinate paper details and forget what they learn in a session. Alpha Hub gives them semantic paper search, AI-generated reports, and persistent annotations — so they get smarter with every task. Search and content powered by [alphaXiv](https://alphaxiv.org).
[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
[![Node.js](https://img.shields.io/badge/node-%3E%3D18-brightgreen)](https://nodejs.org)
## Quick Start
```bash
npm install -g @alpha-hub/cli
alpha login # sign in with alphaXiv
alpha search "attention mechanism" # search papers
alpha get 1706.03762 # fetch paper report
```
## How It Works
Alpha is designed for your coding agent to use (not for you to use!). You can prompt your agent to use it (e.g., "Use the CLI command `alpha` to search for papers on LoRA. Run `alpha` to see how it works.")
**Most of the time, it's simple — search, read, use:**
```bash
alpha search "transformer attention" # find relevant papers
alpha get 1706.03762 # fetch AI-generated paper report
# Agent reads the report, understands the paper. Done.
```
**When the agent discovers something useful**, it can annotate locally for next time:
```bash
alpha annotate 1706.03762 "Superseded by Flash Attention for efficiency"
# Next session, the annotation appears automatically on alpha get.
```
**Need to go deeper?** Ask questions about any paper:
```bash
alpha ask 1706.03762 "What datasets were used for evaluation?"
```
## Commands
| Command | Purpose |
|---------|---------|
| `alpha search <query>` | Search papers (semantic, keyword, or agentic) |
| `alpha get <id\|url>` | Fetch paper report + local annotation |
| `alpha ask <id\|url> <question>` | Ask a question about a paper |
| `alpha annotate <id> <note>` | Attach a note to a paper |
| `alpha annotate <id> --clear` | Remove a note |
| `alpha annotate --list` | List all notes |
| `alpha login` | Sign in with alphaXiv |
| `alpha logout` | Sign out |
All commands accept `--json` for machine-readable output.
## Self-Improving Agents
Alpha Hub is designed for a loop where agents get better over time.
**Annotations** are local notes that agents attach to papers. They persist across sessions and appear automatically on future fetches — so agents learn from past experience.
```
Without Alpha Hub With Alpha Hub
───────────────── ──────────────
Search the web for papers Semantic search via alphaXiv
Read raw PDFs AI-generated paper reports
Miss context and gotchas Agent notes what it learns
Knowledge forgotten ↗ Even smarter next session
↻ Repeat next session
```
## Key Features
### Semantic Search
Three search modes — semantic (embedding similarity), keyword (exact terms), and agentic (multi-turn retrieval) — so agents find the right papers regardless of how they phrase the query.
```bash
alpha search "methods for reducing hallucination in LLMs" # semantic
alpha search "LoRA" --mode keyword # keyword
```
### Paper Q&A
Ask questions about any paper without reading the full PDF. The answer is grounded in the paper's actual content.
```bash
alpha ask 2106.09685 "What is the rank used for the low-rank matrices?"
```
### Annotations
Local notes that agents attach to papers — they persist across sessions and appear automatically on future fetches. See the annotation as a gap the agent discovered and recorded so it doesn't repeat the same mistake.
## License
[MIT](LICENSE)