Extract structured data from files using AI to populate a single metadata template, combining information from multiple documents into one complete record.
MIT
164,225 tools. Last updated 2026-05-31 04:16
"Methods to Extract Data from Files" matching MCP tools:
- Extract structured data from files using custom field definitions. Define fields dynamically to create a single data record from one or multiple documents without requiring pre-existing templates.MIT
- Extract structured data from documents using custom field definitions, combining information from multiple files into a single record with enhanced AI accuracy for complex layouts and low-quality scans.MIT
- Extract structured data from Box files using templates to create single metadata records from one or multiple documents.MIT
- Parse Enforce Script code to extract classes, methods, and enums.MIT
- Extract structured data from audio files using a prompt. Convert spoken content into organized information for analysis and processing.MIT
Matching MCP Servers
- Alicense-qualityCmaintenanceProvides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.Last updatedApache 2.0
- AlicenseAqualityCmaintenanceMCP server for Averra Extract — lets AI agents like Claude, Cursor, and ChatGPT convert any webpage into clean, LLM-ready Markdown.Last updated534MIT
Matching MCP Connectors
Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.
Read-only PostgreSQL, MySQL, SQL Server access via MCP — 24 dialect-aware hosted tools.
- Extract metadata from PDF files using URLs or base64-encoded content to analyze document properties and structure for content processing workflows.MIT
- Extract specific data from JSON files using paths, filters, patterns, or slices to retrieve targeted values, transform data, and analyze specific elements.
- Extract data from Excel xlsx files by specifying sheet, cell range, output format (JSON, CSV, or table), and search criteria. Supports up to 1000 rows with optional headers.
- Extract parameters from web applications to identify potential attack vectors for security testing. Uses automated crawling and manual methods to discover input fields.BSD 3-Clause
- Extract metadata and document information from PDF files to analyze file properties and content structure.
- Extract structured data from web pages by supplying URLs and a prompt, with options for web search and retries.MIT
- Filter JSON data from files or URLs using a shape object to extract specific fields and reduce context size for LLM processing.MIT
- Extract structured data from webpages, HTML, or markdown using AI-powered natural language prompts to get specific information like product details, contact methods, or article metadata.MIT
- Extract clean content from multiple web pages simultaneously to compare information across sources or gather data from several pages at once.Apache 2.0
- Extract files from compressed archives (.zip, .7z, .rar) for malware analysis, automatically trying common passwords if protected.GPL 3.0
- Extract data from Excel sheets and convert to structured JSON with headers and typed rows. Specify sheet index and header presence for precise data extraction.MIT
- Extract data from an Excel sheet and convert it to CSV text. Provide base64-encoded file, optional sheet index (0-based), and delimiter. Returns CSV content for easy data processing.MIT
- Extract social media data from LinkedIn, Instagram, X, or Reddit by providing a URL and choosing the extraction type (likes, comments, profile info, posts, followers). Get targeted data from any supported platform.MIT