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147,770 tools. Last updated 2026-05-27 18:53

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

  • 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
  • Get analysis guidance for EU regulations like GDPR, DORA, and AI Act. Discover delegated acts, proportionality tiers, common pitfalls, cross-regulation pointers, and methodology hints before analyzing regulations.
    Apache 2.0
  • Extract an HTML table into structured data with headers and rows. Ideal for pricing tables, specifications, and financial listings, saving manual cell mapping.
    Apache 2.0
  • Retrieve all tables from the Tulip manufacturing platform to access data on records, machines, stations, and operations.
    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

Matching MCP Servers

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    Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.
    Last updated

Matching MCP Connectors

  • Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.

  • Read-only PostgreSQL, MySQL, SQL Server access via MCP — 24 dialect-aware hosted tools.

  • Retrieve all available tables within a specified Panther Database to understand data structure and log types for security monitoring queries.
    Python
    Apache 2.0
  • Extract text, tables, and image placeholders from DOCX files to access document content programmatically. Use this tool to read Word documents with structured paragraph separation.
    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
  • Create a new table in an OpenL project module, including decision rules, spreadsheets, datatypes, or test tables. Provide the project ID, module name, and complete table structure.
    LGPL 3.0
  • Execute ABAP SQL SELECT queries on database tables and CDS views using SAP ADT Data Preview API for ad-hoc data retrieval, row counts, and filtered queries.
    MIT
  • Retrieve total cost and call count for MCP tool calls made today in UTC, with a readable summary and structured data for analysis.
    MIT
  • Retrieve a list of all tables and views in a specified database. Optionally materialize results as a volatile table for further use.
    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
  • Retrieve table space usage across databases and tables. Filter by database, table name, limit to top N, exclude system tables, or persist results as a volatile table.
    MIT
  • Retrieve detailed time series weather data for any JMA station to analyze trends over hours or days. Customize duration up to one week and select intervals of 10, 30, or 60 minutes for precise analysis.
    MIT
  • Analyze index performance by fetching historical ROI data for specified indices over a defined period. Use start and end dates, pagination, and result limits to evaluate investment trends and make informed decisions.
    TypeScript
  • Scrape Amazon product data with keyword search, parsing, and localization options. Supports currency, geo-location, and auto variant selection for accurate pricing.
    MIT