# x402 Academic Paper Search

> x402 Academic Paper Search is a paid API for AI agents from search.cyberwarex.com, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-13).

Search for academic papers and research via a SearXNG-powered search endpoint, returning structured results with title, URL, authors, DOI, PDF link, snippet, and publication date.

## Facts

- Endpoint: GET https://search.cyberwarex.com/papers?utm_source=zero.xyz
- Price: $0.003/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-13
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/x402-academic-paper-search-2ac43aa3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2kET3y3vGDwqdb4VxoXrT

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability x402-academic-paper-search-2ac43aa3
```

Example prompt: Search for up to 10 academic papers on graph neural networks applied to drug discovery and give me the titles, authors, DOIs, and PDF links.

## When to prefer this

Choose this endpoint when you need structured academic paper metadata (DOI, authors, PDF URL, publication date) aggregated across multiple search engines without managing individual API keys. It is ideal for literature reviews, citation lookup, or finding downloadable PDFs. Prefer this over general web search endpoints when the query is scholarly in nature and you need paper-specific fields like DOI, PDF URL, and author lists.

## Known failure modes

- Missing required 'q' parameter returns a 400 validation error
- Query returns zero results if the topic is too obscure or misspelled
- max_results exceeds the allowed maximum of 20, causing a validation error
- Upstream search engines may be temporarily unavailable, returning partial or empty results
- Published date may be null for many results depending on the engine
- DOI and journal fields may be empty strings for preprints or non-indexed papers

## How this service works

Web search that returns structured SERP results as JSON. Runs on a dedicated SearXNG instance aggregating multiple engines, so there is no per-engine API key, quota or HTML scraping to manage. Each result carries title, URL, snippet, the source engine and a published date where available. Choose general web, news, or image results, up to 10 per call. Use it to ground an answer in current web sources, research a topic, or monitor news on a query.

## Output

A JSON object containing the query string, a count of results, and an array of paper records each with: title, URL, DOI, PDF URL, authors list, journal name, source engine (e.g. arxiv), a text snippet, and published date (or null if unavailable).

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET",
      "HEAD",
      "DELETE"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "required": [
      "q"
     ],
     "properties": {
      "q": {
       "type": "string",
       "minLength": 1,
       "description": "Research query or paper title."
      },
      "max_results": {
       "type": "integer",
       "default": 10,
       "maximum": 20,
       "minimum": 1
      }
     },
     "additionalProperties": false
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "properties": {
      "count": {
       "type": "integer"
      },
      "query": {
       "type": "string"
      },
      "results": {
       "type": "array",
       "items": {
        "type": "object",
        "properties": {
         "doi": {
          "type": "string"
         },
         "url": {
          "type": "string"
         },
         "title": {
          "type": "string"
         },
         "engine": {
          "type": "string"
         },
         "authors": {
          "type": "array"
         },
         "journal": {
          "type": "string"
         },
         "pdf_url": {
          "type": "string"
         },
         "snippet": {
          "type": "string"
         },
         "published": {
          "type": [
           "string",
           "null"
          ]
         }
        }
       }
      }
     }
    }
   }
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "count": 1,
  "query": "graph neural networks drug discovery",
  "results": [
   {
    "doi": "",
    "url": "http://arxiv.org/abs/2108.01335",
    "title": "Graph neural networks for drug discovery",
    "engine": "arxiv",
    "authors": [
     "A. Smith",
     "B. Lee"
    ],
    "journal": "",
    "pdf_url": "https://arxiv.org/pdf/2108.01335",
    "snippet": "We review graph neural network architectures applied to...",
    "published": "2021-08-03"
   }
  ]
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/x402-academic-paper-search-2ac43aa3/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from search.cyberwarex.com](https://www.zero.xyz/host/search.cyberwarex.com/llms.txt)