Roundhouse

Open-Access Paper Full Text

Full text and open-access PDF retrieval for a paper. Given an arXiv id, DOI, OpenAlex id, PMID, or PMCID, returns the readable body split into sections (introduction, methods, results) plus the open-access PDF location: arXiv via ar5iv, biomedical via Europe PMC, OA locations via OpenAlex for the rest. The 'now read it' call after a paper search. Keyless.

SearchLiveeip155:8453Exactvia cdp
https://api.kadec0.xyz/v1/paper-fulltext
Full-textOpen-accessPdf-retrievalPaper-pdfFulltext-api
Calls · 30d
18↑ 8.7%
This endpoint's own trailing-30-day call count, as published by the upstream catalog and snapshotted daily. 30 snapshots so far.
$150.76
Verified settled volume
A floor: summed over 5,000 of 6,757 verified settlements.
$0.040
Listed price
As published in the catalog. Always read the live 402 before paying.
18
Calls · 30d
Upstream's own call count for this endpoint, not ours.
2
Unique payers · 30d
Last called 2026-09-21 01:48Z
—
Upstream on-chain volume
Reported by the source catalog.
Paid to
0x4df66B6c140778fe0717880A7c6dDE5Ea53AcDeA

The wallet the 402 directs payment to. Its whole payment record — every payer, every chain — is on the merchant page.

Asset 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913

Provider

The payTo wallet does not resolve to a registered ERC-8004 agent. That is not a verdict on the service — most of the catalog is unregistered.

Live 402 challenge

Captured by the enrichment pass, not read just now. Prices can change — always read the 402 the endpoint answers with.

{
  "error": "Payment required",
  "accepts": [
    {
      "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
      "extra": {
        "name": "USD Coin",
        "version": "2"
      },
      "payTo": "0x4df66B6c140778fe0717880A7c6dDE5Ea53AcDeA",
      "amount": "40000",
      "scheme": "exact",
      "network": "eip155:8453",
      "mimeType": "application/json",
      "resource": "https://api.kadec0.xyz/v1/paper-fulltext",
      "description": "Full text and open-access PDF retrieval for a paper. Given an arXiv id, DOI, OpenAlex id, PMID, or PMCID, returns the readable body split into sections (introduction, methods, results) plus the open-access PDF location: arXiv via ar5iv, biomedical via Europe PMC, OA locations via OpenAlex for the rest. The 'now read it' call after a paper search. Keyless.",
      "outputSchema": {
        "input": {
          "type": "http",
          "method": "GET",
          "queryParams": {
            "id": {
              "type": "string",
              "description": "arXiv id, DOI, OpenAlex id, PMID, or PMCID"
            },
            "doi": {
              "type": "string",
              "description": "alias for id (DOI form)"
            }
          },
          "discoverable": true
        }
      },
      "maxAmountRequired": "40000",
      "maxTimeoutSeconds": 300
    }
  ],
  "resource": {
    "url": "https://api.kadec0.xyz/v1/paper-fulltext",
    "tags": [
      "full-text",
      "open-access",
      "pdf-retrieval",
      "paper-pdf",
      "fulltext-api"
    ],
    "mimeType": "application/json",
    "description": "Full text and open-access PDF retrieval for a paper. Given an arXiv id, DOI, OpenAlex id, PMID, or PMCID, returns the readable body split into sections (introduction, methods, results) plus the open-access PDF location: arXiv via ar5iv, biomedical via Europe PMC, OA locations via OpenAlex for the rest. The 'now read it' call after a paper search. Keyless.",
    "serviceName": "Open-Access Paper Full Text"
  },
  "extensions": {
    "bazaar": {
      "info": {
        "input": {
          "type": "http",
          "method": "GET",
          "queryParams": {
            "id": "1706.03762"
          }
        },
        "output": {
          "type": "json",
          "example": {
            "count": 1,
            "items": [
              {
                "text": "1 Introduction\nRecurrent neural networks...",
                "type": "paper_fulltext",
                "arxivId": "1706.03762",
                "sections": [
                  {
                    "text": "Recurrent neural networks, long short-term memory...",
                    "heading": "1 Introduction"
                  }
                ],
                "sourceUrl": "https://ar5iv.labs.arxiv.org/html/1706.03762",
                "openAccess": true,
                "fulltextSource": "ar5iv"
              }
            ]
          }
        }
      },
      "schema": {
        "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",
                "anyOf": [
                  {
                    "required": [
                      "id"
                    ]
                  },
                  {
                    "required": [
                      "doi"
                    ]
                  }
                ],
                "required": [],
                "properties": {
                  "id": {
                    "type": "string",
                    "description": "arXiv id, DOI, OpenAlex id, PMID, or PMCID"
                  },
                  "doi": {
                    "type": "string",
                    "description": "alias for id (DOI form)"
                  }
                }
              }
            },
            "additionalProperties": false
          },
          "output": {
            "type": "object",
            "required": [
              "type"
            ],
            "properties": {
              "type": {
                "type": "string"
              },
              "example": {
                "type": "object"
              }
            }
          }
        }
      }
    }
  },
  "x402Version": 2,
  "paymentRequirements": [
    {
      "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
      "extra": {
        "name": "USD Coin",
        "version": "2"
      },
      "payTo": "0x4df66B6c140778fe0717880A7c6dDE5Ea53AcDeA",
      "amount": "40000",
      "scheme": "exact",
      "network": "eip155:8453",
      "mimeType": "application/json",
      "resource": "https://api.kadec0.xyz/v1/paper-fulltext",
      "description": "Full text and open-access PDF retrieval for a paper. Given an arXiv id, DOI, OpenAlex id, PMID, or PMCID, returns the readable body split into sections (introduction, methods, results) plus the open-access PDF location: arXiv via ar5iv, biomedical via Europe PMC, OA locations via OpenAlex for the rest. The 'now read it' call after a paper search. Keyless.",
      "outputSchema": {
        "input": {
          "type": "http",
          "method": "GET",
          "queryParams": {
            "id": {
              "type": "string",
              "description": "arXiv id, DOI, OpenAlex id, PMID, or PMCID"
            },
            "doi": {
              "type": "string",
              "description": "alias for id (DOI form)"
            }
          },
          "discoverable": true
        }
      },
      "maxAmountRequired": "40000",
      "maxTimeoutSeconds": 300
    }
  ]
}

Accepts

The payment requirements as published to the catalog. Read the live 402 before paying — a price here is a claim, not a quote.

0.04USDC≈ $0.04 USD
on Base · exact scheme

Pay 0.04 USDC on Base to 0x4df6…AcDeA. The signed payment is good for 5 minutes.

Paid to
0x4df6…AcDeA
USD Coin contract
0x8335…02913
Payment window
5 minutes
As published
40000 smallest units
The catalog’s raw entry
[
  {
    "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
    "extra": {
      "name": "USD Coin",
      "version": "2"
    },
    "payTo": "0x4df66B6c140778fe0717880A7c6dDE5Ea53AcDeA",
    "amount": "40000",
    "scheme": "exact",
    "network": "eip155:8453",
    "maxTimeoutSeconds": 300
  }
]

Extensions

{
  "bazaar": {
    "info": {
      "input": {
        "type": "http",
        "method": "GET",
        "queryParams": {
          "id": "1706.03762"
        }
      },
      "output": {
        "type": "json",
        "example": {
          "count": 1,
          "items": [
            {
              "text": "1 Introduction\nRecurrent neural networks...",
              "type": "paper_fulltext",
              "arxivId": "1706.03762",
              "sections": [
                {
                  "text": "Recurrent neural networks, long short-term memory...",
                  "heading": "1 Introduction"
                }
              ],
              "sourceUrl": "https://ar5iv.labs.arxiv.org/html/1706.03762",
              "openAccess": true,
              "fulltextSource": "ar5iv"
            }
          ]
        }
      }
    },
    "schema": {
      "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",
              "anyOf": [
                {
                  "required": [
                    "id"
                  ]
                },
                {
                  "required": [
                    "doi"
                  ]
                }
              ],
              "required": [],
              "properties": {
                "id": {
                  "type": "string",
                  "description": "arXiv id, DOI, OpenAlex id, PMID, or PMCID"
                },
                "doi": {
                  "type": "string",
                  "description": "alias for id (DOI form)"
                }
              }
            }
          },
          "additionalProperties": false
        },
        "output": {
          "type": "object",
          "required": [
            "type"
          ],
          "properties": {
            "type": {
              "type": "string"
            },
            "example": {
              "type": "object"
            }
          }
        }
      }
    }
  }
}

Provenance

Seen in the source catalog
2026-09-21 01:48Z
Last indexed by Roundhouse
2026-09-24 10:40Z
Last enriched (probe, favicon, geo)
2026-09-12 18:15Z
x402 version
2
Max timeout
300s
Liveness probe
HTTP 402
Report

Hand this page to an agent

Copy the prompt and paste it into Claude, an MCP client or your own agent — it will vet this service and call it over the free read API. No key, no account.

GET api.roundhouseai.io/v0/endpoints

This endpoint's own trailing-30-day call count, as published by the upstream catalog and snapshotted daily. 30 snapshots so far. Verified volume counts only settlements with an on-chain EIP-3009 marker.

Open skill.md
Show the prompt
Using Roundhouse, look up the x402 service Open-Access Paper Full Text and tell me whether it is
worth paying: what a call costs, whether the endpoint answered when last probed, and what
its payment record actually shows.

curl -s 'https://api.roundhouseai.io/v0/endpoints?q=Open-Access%20Paper%20Full%20Text'
curl -s 'https://api.roundhouseai.io/v0/merchants/<the payTo wallet returned above>'

Then call it: read the price from the live 402 at https://api.kadec0.xyz/v1/paper-fulltext, never from
a cached figure, and pay with an x402 client.

The /v0 API needs an API key (`authorization: Bearer rh_live_…`) on everything except
/v0/unified* and /v0/endpoints. Mint a personal key for $0.01 at GET https://api.roundhouseai.io/v0/test/x402,
or use an organization key from https://roundhouseai.io/dashboard/team.

If you do not have Roundhouse tools or skills installed, read
https://roundhouseai.io/skill.md first — it is the whole procedure.