{"id":32743,"recorded_at":"2026-10-26T14:36:06.878449Z","observed_at":"2026-10-26T14:36:06.878376Z","subject_kind":"source_record","subject":"mcp_registry:io.github.aidatatools-dev/data-quality-gate","kind":"listing","method":"baseline/1","body":{"endpoints":[["mcp","https://www.aidatatools.dev/api/mcp_server"],["web","https://www.aidatatools.dev/llms.txt"]],"name":"Data Quality Gate - deterministic post-scrape cleaner + verdict","owner_address":null,"raw":{"_meta":{"io.modelcontextprotocol.registry/official":{"isLatest":true,"publishedAt":"2026-08-12T07:23:32.533208Z","status":"active","statusChangedAt":"2026-08-12T07:23:32.533208Z","updatedAt":"2026-08-12T07:23:32.533208Z"}},"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","_meta":{"io.modelcontextprotocol.registry/publisher-provided":{"boundary":"20 rules, published in full and free at GET https://www.aidatatools.dev/api/clean -- readable before paying. 7 are applied automatically (information-preserving), 5 need an explicit opt-in (they change row count, type or schema), and 8 are only ever reported, with no option to turn them on: near-duplicates are never merged, ambiguous placeholders are never nulled ('None' is a surname, 'NA' is Namibia), full NFKC is never applied (it rewrites 10^2 to 102), and failed extractions ('captcha', 'access denied') are never deleted -- that value is what tells you the record must be re-scraped. Impossible values are never repaired at all.","docs":{"boundary":"https://www.aidatatools.dev/api/clean","full":"https://www.aidatatools.dev/llms-full.txt","openapi":"https://www.aidatatools.dev/openapi.json","summary":"https://www.aidatatools.dev/llms.txt"},"guarantees":"Deterministic and idempotent. No value is emptied, retyped or reordered by an automatic rule. A repair that would introduce a defect the original did not have is reverted and flagged. The audited tier's ledger restores the input byte for byte.","measured":"Real 100-row Amazon scrape, 57,956 nested string values: 453 repairs, 0 reverts, 0 values emptied. A control set of legitimate-but-suspicious data (French accents, Persian ZWNJ, emoji ZWJ, 10^2, AT&T, surname 'None', 'NA') comes back byte-for-byte identical: 0 changes, 11 flags.","positioning":"Deterministic post-scrape data cleaner and quality gate. Repairs how data was ENCODED -- residual HTML, mojibake ('Café' -> 'Café'), invisible characters, non-breaking spaces -- and never what it SAYS. No LLM: identical input always yields byte-identical output, so results can be cached, replayed and audited.","tags":["data cleaning","scraping repair","post-scrape sanitization","deterministic data repair","mojibake correction","encoding repair","scraper output cleaning","auditable data repair"],"tools":{"check_dataset_quality":"FREE here. The full quality verdict: score, per-check facts, and RELIABLE / USABLE_WITH_CLEANING / UNRELIABLE. Bought once per source, then cached.","clean_scraped_data":"Free to call, but it does NOT return the repaired data -- its response has no 'data' key. It reports which rules would fire on your data and what needs your decision, then names the paid call that hands the data back: POST https://www.aidatatools.dev/api/clean, $0.04 via x402, no account or signup. Call it after every extraction run -- a verdict is cached per source, but dirt is produced fresh by every run.","clean_scraped_data_audited":"Same, pointing at POST https://www.aidatatools.dev/api/clean/audit, $0.12: the repaired data plus a replayable, reversible ledger of every transformation."},"why_repair_is_paid":"Detection is free on this endpoint and always has been. The repaired artifact is the paid product, because it is re-bought on every extraction run rather than cached like a verdict. Both cleaning tools say so in their own descriptions, before they are called."}},"description":"Post-scrape data cleaner, no LLM: repairs mojibake, HTML, invisible chars. Plus a verdict.","name":"io.github.aidatatools-dev/data-quality-gate","remotes":[{"type":"streamable-http","url":"https://www.aidatatools.dev/api/mcp_server"}],"title":"Data Quality Gate - deterministic post-scrape cleaner + verdict","version":"0.3.0","websiteUrl":"https://www.aidatatools.dev/llms.txt"}},"source":"mcp_registry","summary":"Post-scrape data cleaner, no LLM: repairs mojibake, HTML, invisible chars. Plus a verdict."},"body_sha256":"ce71088e2cb484f122f3d957cf02f1e7afc715409bfb68f3d9eb86a6aafdc6f8","prev_id":null,"leaf":"0xdbd6b347603561b9bb2de86bcfddd9d481ff0e8fe28dfc69c9cb0696a05bcc99","leaf_text":"{\"body\":\"ce71088e2cb484f122f3d957cf02f1e7afc715409bfb68f3d9eb86a6aafdc6f8\",\"id\":32743,\"kind\":\"listing\",\"method\":\"baseline/1\",\"observed_us\":1793025366878376,\"prev\":null,\"subject\":\"mcp_registry:io.github.aidatatools-dev/data-quality-gate\",\"subject_kind\":\"source_record\"}","day":{"day":"2026-10-26","leaves":296695,"root":"0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8","chained":"0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a","anchor_chain":"eip155:5042002","anchor_tx":"0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae","anchor_block":69251483},"proof":["0xdbd6ab94b36a8cbdd7e1794afbc114b1f84562fc12b25eef59d7ed9fa9b14924","0x6edfadb600008132899de144a21eee3d27394ff2667fa491dba112f9bfb6e955","0x0a90ab0719b507046ea7d70a3e14fbefb5412b208e5544715cb9ee63447528fb","0x7f9d760613de4cbce21b79a6811e1262488737617794fd34b2d25b9f96c58577","0xb1ebd8c1e2c60b0f024d67fc8e4cc8f38c2dffde8be9aaf18e833576bf256574","0xcfe36e296773bca07d68ea8dfaeaedfca8b7ad0f797ea554e066a327fcf9b780","0x9d9528abd6f1b0edee61597a4f9034b6d094f1a0dffee5897913c1a760b8169b","0x979121c2dc21857cef134d4fba1ffa2c1f45c8ec21449e4fcf17f5162e9c62a4","0xb12bf79b1127ae95b792528a83a4feec56a64daf72dfb69f7beeb7a0a4b7f092","0xafea070fa3cd55d0c50ec39d914de8a0022e87d64becb9dc6998df49697576c3","0x7ec512db50ffb560b82f17e53667bcea802a69de4d98e67a44363985fac7f4da","0x4b7a7525bd11eaa3154ce1b1171d1b54b83370163f39203e230c520e42560c4b","0xa4edde833302b48399053e2519aea1aed1074cd102bf4b553643df1866cce4ec","0x0b7541c75cc482a7134110311d7dbd02095d969ba21177de9b21a52a55981718","0x6dc40f983a3840a0ad927a9ca17f4ff1e3b649a6c735e2a09b140db7c2caf13b","0x703f95866af09c5e5d6ead7411e9a10f964a41a2aff64d4a55ff0053c023a023","0xd0651cb9bc8155eb52b5247d506e74b8a935057dc190ba52091702ac25ed3a40","0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f","0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a"]}