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307,065 tools. Last updated 2026-07-28 03:59

"A tool for parsing tables and analyzing data" matching MCP tools:

  • Discover related tables by analyzing shared key fields to identify parent/child relationships, common join patterns, and related configuration tables in PeopleSoft databases.
    MIT
  • Trigger a historical data resync for specified tables in a Fivetran connection, refreshing only those tables without a full resync.
    MIT
  • Retrieve detailed graph data, including nodes, edges, and statistics, formatted as tables and descriptions. Use to analyze graph structure and gain insights from the Pythagraph RED API.
    ISC
  • Discover all tables in a Hydrolix database, filter by name patterns, and retrieve basic metadata like row counts, sizes, and primary keys for efficient exploration.
    Apache 2.0

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  • Reliable PDF table extraction. Pass a URL, get structured JSON tables with citations.

  • Search the AI Tool Directory catalog: tool details, status checks (alive/acquired/deceased + cause and date), alternatives, and side-by-side comparisons. Read-only.

  • Retrieve all available tables within a specified Panther Database to understand data structure and log types for security monitoring queries.
    Python
    Apache 2.0
  • Generate TQL parsers to convert log events into structured data for security analysis. Analyze JSON, CSV, syslog, or key-value formats to create parsing code with type conversions and schema transformations.
    Apache 2.0
  • Retrieve historical YES price data for any Polymarket market using slug, Gamma ID, or CLOB token ID. Get timestamped price series for charting probability movement and analyzing market efficiency.
    MIT
  • Process AntV-related queries by identifying, parsing, and structuring user requirements for visualization tasks. Extracts topics, detects intent, and prepares structured data for precise solutions.
    MIT
  • Discover available tables and views in a data source to identify data for synchronization jobs. Returns table names in the exact format required for task configuration.
    MIT
  • Reveals tables that co-occur in SQL queries, exposing natural JOIN relationships and data affinity patterns. Use to find related tables or common workflows.
    MIT
  • Scan tables for unusual patterns: volume changes, data gaps, high null rates, and stale data. Detect anomalies with severity-ranked alerts. Automatically samples large tables for efficiency.
    MIT
  • Saves a reusable AI prompt for extracting contract data from raw text, enabling versioned instructions for parsing fields like dates, products, and pricing.
    MIT
  • Extract text and tables from a blob using its unique identifier. Supports synchronous parsing or asynchronous processing with a callback URL for completion.
    MIT