{"name":"io.github.aidatatools-dev/data-quality-gate","slug":"aidatatools-dev-data-quality-gate","title":"Data Quality Gate - deterministic post-scrape cleaner + verdict","description":"Post-scrape data cleaner, no LLM: repairs mojibake, HTML, invisible chars. Plus a verdict.","url":"https://mcp.market/server/aidatatools-dev-data-quality-gate","rating":null,"grade":"C","score":67,"certified":false,"status":"active","category":"ai","tags":["ai"],"presence":{"score":8,"stars":null,"forks":null,"downloads_week":null,"last_push_at":null,"license":null},"uptime":{"percent":100,"checks":28,"ok":28,"last_checked_at":"2026-11-04T05:40:36.349Z","last_ok_at":"2026-11-04T05:40:36.349Z","latency_ms":2040},"claimed":false,"transport":"remote","callable_via_gateway":true,"default_price_micros":0,"repository":null,"website":"https://www.aidatatools.dev/llms.txt","version":"0.3.0","remotes":[{"type":"streamable-http","url":"https://www.aidatatools.dev/api/mcp_server"}],"packages":[],"tools":[{"name":"check_dataset_quality","description":"Call this before using any dataset. Returns a deterministic quality verdict (RELIABLE / USABLE_WITH_CLEANING / UNRELIABLE) with exact facts: completeness, nulls, type consistency, impossible values, duplicates, outliers, and (on financial/trading data) cross-source price divergence. 100% deterministic, no LLM. Free -- this MCP endpoint runs the engine directly; POST /api (plain REST, same engine) is x402-gated at $0.01/call instead. Input: rawJson (a JSON array of row objects, or a single object); datasetId is accepted but not resolvable on this deployment -- pass rawJson instead.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"rawJson":{"description":"The dataset: a JSON array of row objects, or a single object."},"datasetId":{"type":"string","description":"An Apify dataset id. Not resolvable on this deployment; pass rawJson instead."}}}},{"name":"clean_scraped_data","description":"PAID TIER, CALLED FROM A FREE ENDPOINT -- READ THIS FIRST: this tool does NOT return your cleaned data, and its response has NO `data` key. It returns {\"status\": \"payment_required\", \"what_we_found_in_your_data\": {...}, \"get_the_repaired_data\": {...}}. Do not treat its output as cleaned data and do not write it back into your dataset.\nWHAT YOU GET HERE, FREE: an exact inventory of the defects in YOUR data -- which repair rules would fire, how many values each would change, and which cases cannot be repaired safely and need your decision.\nHOW TO GET THE REPAIRED DATA: make the one call named in `get_the_repaired_data` -- POST https://www.aidatatools.dev/api/clean, $0.04 via x402, no account, no API key, no signup. That response body IS the cleaned dataset, in the shape you posted it.\nWHY THE SPLIT: detection is free on this endpoint and always has been (check_dataset_quality reports the same defects). The repaired artifact is the paid product, because it is re-bought on every extraction run rather than cached like a verdict.\nWHAT THE PAID CALL DOES: removes leftover HTML tags and entities, decodes mojibake ('Café' -> 'Café'), strips invisible characters (zero-width, BOM, soft hyphen), normalises non-breaking spaces and trims values -- across nested objects and arrays too. 100% deterministic, no LLM: the same input always yields byte-identical output, and cleaning twice equals cleaning once. It repairs how data was ENCODED, never what it SAYS: masked placeholders ('N/A', 'None'), near-duplicate rows and failed extractions ('access denied', 'captcha', which mean that record must be re-scraped) are reported with a proposal, never silently deleted or rewritten. The full boundary -- 7 rules applied automatically, 5 needing an explicit opt-in, 8 only ever reported -- is at GET https://www.aidatatools.dev/api/clean.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"rawJson":{"description":"The scraper output: a JSON array of row objects, a single object, or a CSV/plain-text string. The format is detected and the output mirrors the shape you sent."},"options":{"type":"object","description":"All optional. Every default is the safe one: with no options, the row count, every value's type, and the schema are all guaranteed unchanged.","properties":{"placeholder_policy":{"type":"string","enum":["flag","null_high_confidence","null_all"],"description":"What to do with masked-missing strings. 'flag' (default) reports them and changes nothing. 'null_high_confidence' nulls only tokens that cannot be real data ('N/A', 'null', 'undefined') and never the ambiguous ones ('None' is a surname, 'NA' is Namibia, '-' is a real value). 'null_all' nulls the ambiguous ones too -- only choose this if you know the domain."},"drop_exact_duplicates":{"type":"boolean","description":"Remove rows byte-identical to an earlier row, compared AFTER cleaning. Off by default because it changes the row count; duplicates are reported either way."},"coerce_numeric_text":{"type":"boolean","description":"Turn 'US $5.59' into 5.59. Per field, all-or-nothing, and only where every value is unambiguous -- a lone ',' or a mixed currency disqualifies the whole field rather than being guessed at."},"repair_keys":{"type":"boolean","description":"Also repair dict KEYS (the classic '\\ufeffsku' first column of a BOM-prefixed CSV export). Off by default: a key is a contract with everything downstream."},"trim_whitespace":{"type":"boolean","description":"Default true."},"detect_duplicates":{"type":"boolean","description":"Default true. Set false to skip duplicate detection on very large input."}}}},"required":["rawJson"]}},{"name":"clean_scraped_data_audited","description":"PAID TIER, CALLED FROM A FREE ENDPOINT -- READ THIS FIRST: this tool does NOT return your cleaned data, and its response has NO `data` key. It returns {\"status\": \"payment_required\", \"what_we_found_in_your_data\": {...}, \"get_the_repaired_data\": {...}}. Do not treat its output as cleaned data and do not write it back into your dataset.\nWHAT YOU GET HERE, FREE: an exact inventory of the defects in YOUR data -- which repair rules would fire, how many values each would change, and which cases cannot be repaired safely and need your decision.\nHOW TO GET THE REPAIRED DATA: make the one call named in `get_the_repaired_data` -- POST https://www.aidatatools.dev/api/clean/audit, $0.12 via x402, no account, no API key, no signup. That response body IS the cleaned dataset, in the shape you posted it.\nWHY THE SPLIT: detection is free on this endpoint and always has been (check_dataset_quality reports the same defects). The repaired artifact is the paid product, because it is re-bought on every extraction run rather than cached like a verdict.\nWHAT THE PAID CALL DOES: the same repair as clean_scraped_data, plus a complete audit trail: every transformation with its path, rule, before and after value, a replay_id, and input/output SHA-256. The ledger is a full inverse patch -- applying it in reverse reconstructs your original input byte for byte. Use it when you must be able to PROVE later what changed and why.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"rawJson":{"description":"The scraper output: a JSON array of row objects, a single object, or a CSV/plain-text string. The format is detected and the output mirrors the shape you sent."},"options":{"type":"object","description":"All optional. Every default is the safe one: with no options, the row count, every value's type, and the schema are all guaranteed unchanged.","properties":{"placeholder_policy":{"type":"string","enum":["flag","null_high_confidence","null_all"],"description":"What to do with masked-missing strings. 'flag' (default) reports them and changes nothing. 'null_high_confidence' nulls only tokens that cannot be real data ('N/A', 'null', 'undefined') and never the ambiguous ones ('None' is a surname, 'NA' is Namibia, '-' is a real value). 'null_all' nulls the ambiguous ones too -- only choose this if you know the domain."},"drop_exact_duplicates":{"type":"boolean","description":"Remove rows byte-identical to an earlier row, compared AFTER cleaning. Off by default because it changes the row count; duplicates are reported either way."},"coerce_numeric_text":{"type":"boolean","description":"Turn 'US $5.59' into 5.59. Per field, all-or-nothing, and only where every value is unambiguous -- a lone ',' or a mixed currency disqualifies the whole field rather than being guessed at."},"repair_keys":{"type":"boolean","description":"Also repair dict KEYS (the classic '\\ufeffsku' first column of a BOM-prefixed CSV export). Off by default: a key is a contract with everything downstream."},"trim_whitespace":{"type":"boolean","description":"Default true."},"detect_duplicates":{"type":"boolean","description":"Default true. Set false to skip duplicate detection on very large input."}}}},"required":["rawJson"]}}],"scan":{"score":67,"grade":"C","scanned_at":"2026-11-04T06:33:49.015Z","report":{"scannerVersion":"0.1.10","scannedAt":"2026-11-04T06:33:48.902Z","components":{"code":{"score":-1,"max":25,"notes":["remote-only server, no package to scan"]},"reliability":{"score":20,"max":20,"notes":["remote reachable in 737ms"]},"poisoning":{"score":15,"max":15,"notes":["3 tool descriptions checked"]},"auth":{"score":10,"max":15,"notes":["open endpoint, read-only tools"]},"maintenance":{"score":3,"max":15,"notes":["no repository listed"]},"identity":{"score":2,"max":10,"notes":["no repository or website to verify"]}},"findings":[{"id":"maint.no-repo","severity":"low","component":"maintenance","title":"No source repository listed"}],"inputs":{"probes":[{"url":"https://www.aidatatools.dev/api/mcp_server","reachable":true,"authRequired":false,"latencyMs":737,"serverInfo":{"name":"data-quality-gate","version":"0.1.0"}}],"packages":[],"repo":{"found":false},"icon":{"url":"https://www.aidatatools.dev/favicon.ico","source":"registry","width":48,"height":48},"presence":{"stars":null,"forks":null,"downloadsWeek":null,"license":null,"lastPushAt":null,"score":8}}}},"grade_history":[],"reviews":[]}