Metadata-Version: 2.4
Name: priorwork-mcp
Version: 0.1.0
Summary: MCP server for priorwork.fyi — academic ML paper search for Claude Code and Cursor
Project-URL: Homepage, https://priorwork.fyi
Project-URL: Repository, https://github.com/stefanmagureanu/Steference-review
License: MIT
Keywords: academic-search,machine-learning,mcp,model-context-protocol,papers,semantic-search
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Requires-Dist: httpx>=0.24.0
Requires-Dist: mcp>=1.2.0
Description-Content-Type: text/markdown

# priorwork-mcp

MCP server for [priorwork.fyi](https://priorwork.fyi) — semantic search over 114,000+ papers
from major ML, NLP, and Computer Vision conferences (NeurIPS, CVPR, ICML, ICLR, ACL, EMNLP,
ICCV, AISTATS, and more), directly from Claude Code, Cursor, or any MCP client.

## Tools

| Tool | Description |
|---|---|
| `search_papers` | Semantic search from a natural-language query — returns ranked papers with authors, venue, year, similarity score, download URL, and abstract snippet |
| `search_by_pdf_url` | Give it a public PDF link (e.g. an arXiv PDF) and get semantically similar papers from the index |
| `list_indexes` | List the available paper indexes and their sizes |

## Setup

### Claude Code

```bash
claude mcp add priorwork -- uvx priorwork-mcp
```

### Cursor / other MCP clients

Add to your MCP configuration:

```json
{
  "mcpServers": {
    "priorwork": {
      "command": "uvx",
      "args": ["priorwork-mcp"]
    }
  }
}
```

## Configuration

Configuration is via environment variables (pass with `-e KEY=value` in `claude mcp add`,
or an `"env"` block in JSON configs):

| Variable | Required | Description |
|---|---|---|
| `PRIORWORK_API_KEY` | No | API key from priorwork.fyi (enables authenticated features) |
| `PRIORWORK_API_URL` | No | Override the API base URL (default `https://priorwork.fyi`) |

## Example

> "Find prior work on spatiotemporal forecasting with graph neural networks"

```
1. Taming Local Effects in Graph-based Spatiotemporal Forecasting — Andrea Cini, et al. (2023 · NeurIPS)  [score: 0.802]
2. FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective — ...
```

## License

MIT
