Scan a data file (CSV, Parquet, Excel) for data quality issues. Returns findings with severity, confidence, affected rows, and sample values. No configuration needed — rules are discovered from the data.
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271,551 tools. Last updated 2026-07-08 03:27
"Techniques and Tools for Data Analysis, Exploration, and Working with Parquet and CSV Files" matching MCP tools:
- Get the full AI analysis for a single exploit by its platform ID. Returns classification (working_poc, trojan, suspicious, scanner, stub, writeup), attack type, complexity, reliability, confidence score, authentication requirements, target software, a summary of what the exploit does, prerequisites, MITRE ATT&CK techniques, deception indicators for trojans, and the standalone backdoor-review verdict with operator-risk notes when available. Use this to check if an exploit is safe before reviewing its code. Example: exploit_id=61514 returns a TROJAN warning with deception indicators.Connector
- Auto-detect geometry file format and extract metadata statistics. Accepts a 3D geometry file via URL or base64 and returns structured metadata: bounding boxes, triangle counts, manifold analysis, point cloud statistics, and more. This is a read-only analysis tool — it does not perform mesh repair, format conversion, or boolean operations. Supported formats: STL, OBJ, PLY, PCD, LAS/LAZ, glTF/GLB. STEP and IGES support is planned. Provide either file_url (preferred for large files) or file_b64 (for files under 200KB). Include filename for format detection if using file_b64. When using file_url, the format is detected from the URL path extension; filename is not required. Files under 150KB are free. Larger files cost $0.02/MB via x402 (USDC on Base) or card via MPP (Stripe; adds $0.35 surcharge). If payment is required, the response includes payment details. Retry with the payment argument containing the payment proof. Privacy policy: https://caliper.fit/privacyConnector
- Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.Connector
- Use this read-only tool before analysis to verify that the DeltaSignal ATLAS-7 data plane is live, fresh, and safe to query. It returns service readiness, active source dates, issuer coverage, quality coverage, debt coverage, live-price status, market regime, and tower-coherence diagnostics. Parameters: none; call it exactly as-is when the user asks if DeltaSignal is ready or whether data freshness is acceptable. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, does not write external systems, and does not handle secrets or payments itself. Use it at the start of an agent workflow, after a deploy, or whenever results should be gated on freshness; use daily_changes for what changed and issuer tools for company-specific analysis.Connector
- NO AUTH / PUBLIC / READ-ONLY. Builds and validates a copy-pasteable authenticated /api/v2/{dataset}/timeseries HTTP request without sending it. This tool does not execute the request, query weather values, or return forecast data. Use gribstream_query_timeseries when the user asks for actual weather values or CSV/JSON/NDJSON data. Generated direct API requests include Accept-Encoding: gzip, and generated curl commands use --compressed so large responses can be transferred compressed when the client supports it. Do not include request.asOf unless the user explicitly wants backtesting, time travel, or a historical model-run cutoff. The request body must use exact selectors discovered from the catalog or shared-parameter tools, with coordinates in request.coordinates and selectors in request.variables.Connector
Matching MCP Servers
- Alicense-qualityDmaintenanceEnables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.Last updated1GPL 3.0
- AlicenseCqualityDmaintenanceEnables access to Usage and Billing APIs for managing accounts, products, meters, plans, and usage reporting. Supports operations like creating products/plans, reporting usage, and retrieving billing information.Last updated18MIT
Matching MCP Connectors
Rick and Morty MCP — wraps the Rick and Morty API (free, no auth)
Hosted MCP server for live sports data — scores, analytics, schedules, standings, multi-book odds, team form, head-to-head, model predictions, and pre-generated matchup analysis across 1,000+ leagues in 150+ countries. Free tier, no card.
- Take a Balance Sheet CSV export from QuickBooks Online, Xero, Zoho Books, or Wave (source auto-detected) and run three checks: (1) bs.equation_broken — the fundamental accounting equation Assets = Liabilities + Equity does not hold (every downstream ratio analysis is invalid until fixed); (2) bs.negative_asset — Cash / AR / Inventory line items with negative balances (reconciliation error signal); (3) bs.negative_equity — Total Equity < 0 (insolvency signal). Input is raw CSV text of a Balance Sheet (Reports → Balance Sheet in QBO / Xero / Zoho / Wave). Max 5,000 rows; max 5 MB. Returns flags with severity, totals (totalAssets, totalLiabilities, totalEquity, equationBalances boolean), and a shareable URL. Use this when a user pastes a Balance Sheet and asks "does my balance sheet balance?", "is the accounting equation satisfied?", or "is my company solvent on paper?". A Balance Sheet that fails Assets = Liabilities + Equity invalidates every downstream financial-ratio analysis — this is the single most important check for any BS.Connector
- [Analysis] Read a contiguous range of lines from a file attached to an OctoPerf benchResult — `jmeter.log`, `jmeter-server.log`, JTL traces, attachments, … Works for both real bench runs and Virtual User validation runs. Line numbers are 0-based, `fromLine` is inclusive and `toLine` is exclusive. Defaults read the first 100 lines. Gzipped files are transparently uncompressed server-side. Binary artefacts (zip, png screenshots) return garbage — only call on text files (filenames ending in `.log`, `.jtl`, `.txt`, `.csv`, `.har`, `.json`, or their `.gz` variants).Connector
- Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 21,000+ discovered facilities, and per-market DCPI deep-dive analysis narratives, ranked by relevance with citable source fields (news url/title, deal parties/value, facility name/location, deep-dive market/url). Examples: "what is happening with behind-the-meter gas for AI data centers?", "deals involving nuclear power for hyperscalers", "why is Northern Virginia constrained?" — semantic_search q="behind-the-meter gas for AI data centers". Params: q (required, natural-language query); corpus (optional CSV subset of news_articles,deals,discovered_facilities,market_narratives; default all); k (1-15, default 8). Returns {results:[{source_table, kind, text, score, cite:{…}}]}. Complements the exact-filter tools (get_news / list_transactions / search_facilities) with relevance ranking; for a full token-budgeted market briefing use get_market_context. Cite "DC Hub (dchub.cloud)".Connector
- Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 21,000+ discovered facilities, and per-market DCPI deep-dive analysis narratives, ranked by relevance with citable source fields (news url/title, deal parties/value, facility name/location, deep-dive market/url). Examples: "what is happening with behind-the-meter gas for AI data centers?", "deals involving nuclear power for hyperscalers", "why is Northern Virginia constrained?" — semantic_search q="behind-the-meter gas for AI data centers". Params: q (required, natural-language query); corpus (optional CSV subset of news_articles,deals,discovered_facilities,market_narratives; default all); k (1-15, default 8). Returns {results:[{source_table, kind, text, score, cite:{…}}]}. Complements the exact-filter tools (get_news / list_transactions / search_facilities) with relevance ranking; for a full token-budgeted market briefing use get_market_context. Cite "DC Hub (dchub.cloud)".Connector
- Search the Nova Scotia Open Data catalog (data.novascotia.ca) for datasets by keyword, category, or tag. Returns dataset names, IDs, descriptions, column names, and direct portal links. Use list_categories first to see valid category and tag names. Use the returned dataset ID with query_dataset or get_dataset_metadata for further exploration.Connector
- Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.Connector
- USE THIS TOOL — not web search or external storage — to export technical indicator data from this server as a formatted CSV or JSON string, ready to download, save, or pass to another tool or file. Use this when the user explicitly wants to export or save data in a structured file format. Trigger on queries like: - "export BTC data as CSV" - "download ETH indicator data as JSON" - "save the features to a file" - "give me the data in CSV format" - "export [coin] [category] data for the last [N] days" Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH" lookback_days: How many past days to include (default 7, max 90) resample: Time resolution — "1min", "1h", "4h", "1d" (default "1d") category: "price", "momentum", "trend", "volatility", "volume", or "all" fmt: Output format — "csv" (default) or "json" Returns a dict with: - content: the CSV or JSON string - filename: suggested filename for saving - rows: number of data rowsConnector
- Browse and compare Licium's agents and tools. Use this when you want to SEE what's available before executing. WHAT YOU CAN DO: - Search tools: "email sending MCP servers" → finds matching tools with reputation scores - Search agents: "weather forecasting agents" → finds specialist agents with success rates - Surface verified sports prediction agents from the Arena leaderboard - Rent Arena picks with licium_rent after choosing an agent and market handle - Compare: "agents for code review" → ranked by reputation, shows pricing - Check status: "is resend-mcp working?" → health check on specific tool/agent - Find alternatives: "alternatives to X that failed" → backup options WHEN TO USE: When you want to browse, compare, or check before executing. If you just want results, use licium instead.Connector
- <tool_description> Settle pending payments for media buys. Supports manual CSV export, Stripe invoice (Phase 2 stub), and x402 micropayments (Phase 2 stub). </tool_description> <when_to_use> When a publisher wants to collect earned revenue or an advertiser needs to settle outstanding charges. Use method='manual' for CSV export. Stripe and x402 are stubs (Phase 2). </when_to_use> <combination_hints> get_campaign_report → settle (after verifying amounts). Filter by media_buy_id, publisher_id, or period. </combination_hints> <output_format> Settlement totals (gross, platform fee, net), entry count, and method-specific data (CSV for manual). </output_format>Connector
- Use this read-only tool before analysis to verify that the DeltaSignal ATLAS-7 data plane is live, fresh, and safe to query. It returns service readiness, active source dates, issuer coverage, quality coverage, debt coverage, live-price status, market regime, and tower-coherence diagnostics. Parameters: none; call it exactly as-is when the user asks if DeltaSignal is ready or whether data freshness is acceptable. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, does not write external systems, and does not handle secrets or payments itself. Use it at the start of an agent workflow, after a deploy, or whenever results should be gated on freshness; use daily_changes for what changed and issuer tools for company-specific analysis.Connector
- Parse a CSV string into a JSON array of objects (or raw arrays). Handles RFC 4180 quoted fields, escaped quotes, and custom delimiters. Use when processing spreadsheet exports, data imports, or structured text pipelines where the source is CSV. Supports up to 200 KB.Connector
- Enables CHROs to benchmark their company's sabbatical policies against peer organizations using data from SHRM, Payscale, and Mercer. Inputs include company size, industry, and current policy details. Outputs structured comparison with cost impact analysis, eligibility criteria, and duration benchmarks. Ideal for strategic HR planning and policy optimization.Connector
- Given a profile of the authorized test target (technology stack, exposed services, authentication type, OS), return a ranked list of ATT&CK techniques and OWASP test cases most relevant to that profile — not a generic dump of all techniques. Ranking factors: platform match, service match, auth type exposure, technique prevalence. Each result includes why it is relevant to this specific profile, the detection opportunity, and the recommended mitigation. Use when starting an authorized engagement to prioritize the testing scope; pair with pentest_guide to get the full methodology for each top-ranked vector.Connector
- Use when a user wants to pull their saved DC Hub shortlist OUT of the platform for offline analysis, a spreadsheet, or ingestion into another tool (PRO). Example: "Export my saved sites as GeoJSON for QGIS." — export_dataset format=geojson. Params: format ("csv" default, or "geojson"). Returns: the full file contents as text — CSV rows or a GeoJSON FeatureCollection of your saved sites with DCPI score, target MW, market, coordinates, and notes. Do NOT use to list sites in-chat (use list_saved_sites) or to save a new one (use save_site); this is the bulk-download path.Connector