"Automated error detection in transformation processes" matching MCP tools:

• transform_image

  Uploadkit

  Generate a CDN-cached image variant for a file stored in UploadKit Cloud. Requires a paid plan, a live API key in the MCP process environment as UPLOADKIT_API_KEY, and an image key returned by UploadKit. BYOS files are not supported. Use signed delivery for private or temporary content and public delivery for stable URLs in websites, apps, srcset, CSS, or stored application data. Explicit formats consume 1 transformation unit; auto consumes 3 units. When to use: after an image is uploaded and the user wants a resized, cropped, optimized, or converted delivery URL. The returned URL is safe to send to browsers; the API key remains server-side. Returns: JSON { url, expiresAt, delivery, transform, usage }. Has the side effect of reserving monthly transformation units for a new unique variant.

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• find_error_patterns

  ALM X++ MCP Server

  WHEN: a user encounters an error message, infolog error, or runtime exception in D365. Also handles business-language error explanation when audienceType='business'. Triggers (developer): 'fix this error', 'what causes', 'exception thrown', 'infolog error', 'update conflict', 'outside tts', 'number sequence'. Triggers (business): 'what does this error mean', 'explain this error to me', 'user gets error X', 'que signifie cette erreur', 'message d\'erreur', 'what should the user do when they see this error'. Find known D365 F&O error patterns matching an error message or symptoms description. Matches against a built-in database of common errors (transaction conflicts, security issues, number sequences, posting errors, batch problems, etc.), resolves D365 label IDs from error text (e.g. user sees 'Number sequence not set up' -> finds @SYS70535 -> finds the throwing code), and searches the indexed codebase. Returns root causes, step-by-step resolution, label matches, and source code locations. [~] When the error text contains a D365 label ID (e.g. '@SYS12345'), call `search_labels` first to resolve the label text, then call this tool with the resolved text. Set audienceType='business' for a plain-language explanation targeted at end users instead of developers.

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• index_video

  Reka

  Index a video for search, QA, or full analysis. Processes the video through a pipeline of AI features. Typically takes 3-7 minutes; longer for long videos or the 'full' pipeline. Times out after 10 minutes by default. Pipelines: - search_only: transcription + captions + embeddings (enables search_videos) - qa_only: transcription + captions (enables ask_video) - full: transcription + captions + embeddings (enables all tools) Scene detection is enabled by default and produces scene boundaries for get_scenes. Pass scene_detection=False to skip it. Prerequisites: if using video_id, the video must be in 'uploaded' status. Use get_video to check status before calling this tool.

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• transform_text

  rnv-color-mcp

  Apply an exact, deterministic text transformation. operation is one of: UPPERCASE, lowercase, 'Title Case', 'Sentence case', camelCase, PascalCase, snake_case, CONSTANT_CASE, kebab-case, dot.case, 'iNVERTED cASE'. Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly. Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.

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• list_topics

  flevy

  The canonical list of management topics Flevy's catalog is organized under, each with its known aliases (e.g. "Digital Transformation" and "Digital Transformation Strategy" may be the same topic) and content counts. Use this to map a user's phrasing to the exact topic filter accepted by search_content, or to show what subject areas Flevy covers.

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• bulk_sigma_rule_lookup

  ContrastAPI

  Bulk Sigma rule lookup — retrieve full records for up to 50 rule UUIDs in a single request instead of N separate sigma_rule_lookup calls. Designed for triage workflows where multiple rule ids are known (e.g., from a SIEM alert batch or a tagged detection bundle). Each item is the same shape as sigma_rule_lookup with status ok/not_found/invalid_format and an error field when applicable. Up to 50 rule ids per call (same cap for Free and Pro). Each rule_id consumes 1 unit of the hourly quota; ids beyond the caller's remaining quota land in skipped_due_to_rate_limit instead of failing the whole batch (parity with bulk_cve/ioc). Free: 30/hr, Pro: 500/hr. Returns {results [{rule_id, status, rule, error}], total, processed, skipped_due_to_rate_limit, successful, failed, partial, summary, next_calls}.

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• unpublish_workflow

  Dreamlit

  Use after explicit user intent to unpublish a Dreamlit workflow. Side effect: disables live triggers or schedules for that workflow and stops future automated sends. Returns updated workflow status and app URLs. Do not use for deleting drafts, canceling one broadcast run, or editing workflow content.

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• book_demo

  gethal.ai

  Submits a demo request. The prospect receives a confirmation email and must click the link in it before the request reaches a human at A Cloud Frontier. Use only when a real person has explicitly asked for a demo and provided their own working email address. Do NOT call this for testing, evaluation, or crawling purposes — automated and unconfirmable requests are rejected.

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• transform_text

  rnv-color-mcp

  Apply an exact, deterministic text transformation. operation is one of: UPPERCASE, lowercase, 'Title Case', 'Sentence case', camelCase, PascalCase, snake_case, CONSTANT_CASE, kebab-case, dot.case, 'iNVERTED cASE'. Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly. Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.

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• paraguay_search_tenders

  Paraguay Dncp

  Search Paraguay government procurement processes (tenders/contracts) from the official DNCP Open Contracting (OCDS) API. Results are date-scoped: the API requires a date range, so if you omit date_from/date_to it defaults to roughly the last 30 days. Returns a paginated list of processes with ocid, id, title, buyer (convocante), procurement method, and dates. Field values are in Spanish; monetary amounts are in PYG. Detailed value/status/items live in the full record — pass an id to paraguay_get_record. Note: the API has no free-text search parameter, so "query" is applied as a case-insensitive client-side filter over the current page of results.

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• search_businesses

  knowledge-base

  Find businesses, merchants and websites in the tunnel knowledge base by name or topic. Start here: every other tool needs a `slug`, and this is where a `slug` comes from. Returns an array of summaries, each with `slug`, `kind`, name, description and a `verification` object. Read `verification.level` rather than assuming: "human" means a tunnel employee checked the business, "automated" means machines proved only that the business controls its own channels, and null means neither. Zero matches is a normal answer, not an error — it comes back with `completeness` "empty". Authentication: none. This tool works with no credentials.

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• ios_crash_analytics

  Robot Actions — Remote Device Control

  List crash reports on an iOS device with aggregate analytics (total, per-app, per exception type, per-day timeline). Telemetry and in-house automation processes are excluded. Use ios_crash_detail with a returned crash id for the full log. No automation session required.

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• find_chicago_comparable_sales

  Cook County / Chicago Property Data

  Recent arm's-length comparable sales (comps) in the same Cook County assessor neighborhood and property class as the given PIN, with an implied low/median/high price range — a derived, lightweight automated valuation you won't get from a raw open-data query. Costs $0.10 per call (x402, USDC) — the highest-value route; try get_free_sample first.

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• convert_code

  Jinero

  Convert code between text formats (e.g. JSON↔YAML, CSS↔SCSS). Pure text transformation: the source is parsed and re-serialized, never executed and never stored. Use list_code_converters for valid from/to ids and per-converter options.

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• validate_task_contract

  Reality Graph Verification Tools

  Deterministically validates a FILLED task contract (the JSON structure from get_task_contract_template): completeness of goal/non-goals/boundaries, decidability of each acceptance criterion (vague words, missing measurable markers), automated checks in the validation plan, expected evidence, and leftover placeholders. Returns a verdict (PASS / PASS WITH WARNINGS / FAIL), four dimension scores, and a concrete fix per finding. Validates form and completeness, not correctness. No LLM, nothing stored. lang='de' for German.

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• check_upgrade_safety

  Breaking Changes & Migration Data

  Given a package and the version you are upgrading TO, return a concise checklist an agent can act on: the count of breaking changes, the highest-risk removals, whether automated codemods exist, and the recommended upgrade path. Use before performing an upgrade.

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• clean_scraped_data_audited

  Data Quality Gate - deterministic post-scrape cleaner + verdict

  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. WHAT 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. HOW 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. WHY 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. WHAT 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.

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• validate_codes

  Medical Terminologies MCP

  Validate a mixed batch of medical codes against their source terminologies. Useful for retrospective analysis of legacy databases — flag codes that no longer exist, surface ICD-10 → ICD-11 replacements, and grade activity status where the terminology exposes it. For each input `{ code, terminology }`, returns: - **valid**: whether the code exists in the source terminology. - **active**: whether the code is currently active. Null when the source doesn't expose an explicit active/inactive distinction at category level (CID-10, ATC, ICD-11, RxNorm, MeSH all return null today; SNOMED and LOINC return a real boolean). - **title**: the official label/name when available. - **replaced_by**: a successor code, populated today only for ICD-10 codes that have a primary ICD-11 mapping in the bundled WHO transition tables. - **source**: human-readable provenance of the validation (terminology + release/version). - **error**: non-null only when validation couldn't be performed (network error, SNOMED feature flag off, etc.). `valid: false` + `error: null` means "code not found"; `valid: false` + `error: set` means "couldn't validate". Terminology is **required per code** — auto-detection isn't supported because category codes like "A00" exist in both ICD-10 and CID-10. Accepted values: `icd11`, `icd10`, `snomed`, `loinc`, `rxnorm`, `mesh`, `atc`, `cid10`. Hard cap of 50 codes per call; codes are validated in parallel through their respective clients, so total wall time scales with the slowest upstream + its rate limit (worst case ~10 s for a full batch hitting ICD-11).

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• get_topic_details

  flevy

  An end-to-end overview of one management topic: its definition, an in-depth explanation of the discipline, the 3 editor-curated top documents, all known aliases, document and case study counts, related topics, and the topic page URL. Use this to survey a discipline before going deep — e.g. "what does Digital Transformation cover and what are its key frameworks" — or to orient when the user describes a broad problem area. Follow with search_content (topic filter) for the full catalog.

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• list_error_codes

  Trillboards DOOH Advertising

  List every error code in the Trillboards API error catalog. WHEN TO USE: - Understanding what error codes the API can return. - Building a client-side error handler that covers all cases. - Looking up error types, HTTP statuses, and documentation URLs. RETURNS: - object: "list" - data: Array of { code, type, http_status, description, doc_url } - total: Total number of error codes. Equivalent to GET /v1/errors but executed in-process (no HTTP round-trip). EXAMPLE: Agent: "What error codes can the API return?" list_error_codes()

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