Datasets:

x402Fizzl
/

x402-trust-index

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 342, in _generate_tables
                  df = pandas_read_json(f)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                  ~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4645, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2866, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3073, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2581, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 345, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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x402 Trust Index

Every paid x402 and MPP API endpoint that public indexes list, checked once a day the way a paying AI agent would: can an agent pay it today, at the advertised price, to an address that can receive, and how often could it over the last 30 days. Built by x402 Doctor (Fizzl).

Scan of 2026-10-26: 70,792 endpoints, 69,412 (98.1%) payable as listed. Daily history since 2026-09-27. Updated after every daily scan.

Files

data/endpoints.jsonl, one row per endpoint in the latest scan:
- url, host, method, protocol (x402 or mpp)
- verdict: go (payable as listed), caution (payable, with a detail some clients refuse) or no_go (an agent should not pay it)
- reasons: the check codes behind the verdict, such as no_402, resource_mismatch, testnet_only, price_above_advertised or payto_sanctioned
- price_usd: the cheapest payable price per call
- networks: the CAIP-2 networks the endpoint can be paid on today; unpayable_networks: networks it offers but that can't be paid (for example a Stellar asset given as text)
- category: the kind of service (crypto, security, onchain, ai, search, finance, media, places, social, dev, data), from TypeSafe Jev or a keyword guess
- same_service_endpoints: how many of the seller's endpoints are the same service (one per coin, city or ticker)
- days_checked, days_payable, payable_ratio, and history: one letter per day, oldest first (g go, c caution, n no_go, x error, - not listed that day)
- description: the seller's own description, cut at 300 characters
data/daily.csv: date, go, caution, no_go, checked for every day in the history.
data/spot_buys.jsonl: what came back when x402 Doctor actually paid. Every week it buys a random sample of up to 30 endpoints that are go here (one per seller, at most $0.05 each, USDC on Base, from a dedicated wallet) with the example input from the seller's own listing. 82 purchases so far:
- date, run, url, host, price_usd, charged_usd (measured on chain)
- result: delivered, off_schema (an answer that doesn't match the declared schema), empty, charged_not_delivered, payment_rejected (asked to pay again, not charged), error_not_charged or payment_failed
- status, reason, answer_s (seconds from the first request to the paid answer), timed_out, request (example: the listing's own example input)
data/onchain_payments.csv: real payments. Per payout address in this index and per UTC day (the last 8), the USDC payments on Base that the payer signed with EIP-3009 (transferWithAuthorization, the way x402 settles USDC): date, pay_to, payments, usd, payers (different paying wallets), and day_coverage (the share of that day's blocks that were read). Plain transfers, Permit2 and Circle Gateway batches don't count; x402 Doctor's own test wallet is left out.

How it is collected

Sources: the CDP Bazaar, Circle's Agent Marketplace, the MPP directory, GoPlausible, the XRPL AI Hub, nohumans.directory's catalogue (CC BY 4.0), PayAPI Market and other public x402 indexes.
The check: each endpoint is called once a day without paying. Its 402 challenge is parsed and checked the way a paying agent would: a valid challenge, the price against the listing, the network and token, whether the payout address can receive (Solana token accounts, Algorand opt-in, XRP Ledger and Stellar trustlines), testnet-only offers, and OFAC screening of the payout address (OFAC SDN list, published 2026-10-21). Nothing is paid.
Caveat: a sudden jump usually means one large seller went down or changed, since one seller can list tens of thousands of endpoints.

Use it

from datasets import load_dataset
endpoints = load_dataset("x402Fizzl/x402-trust-index", "endpoints", split="train")

One endpoint's live record: GET https://x402-doctor.fizzl.eu/api/trust?url=<endpoint> (free)
Before paying an endpoint: GET https://x402-doctor.fizzl.eu/api/v1/preflight?url=<endpoint> ($0.001, go / caution / no_go)
What the data shows: x402 health report, October 2026 · The seven most common x402 seller mistakes · x402 on Stellar
How AI agents handle payment traps: x402 Agent Safety Bench
The same files on GitHub: Fizzl13/x402-doctor, trust-data branch