"Extracting Orders from PDF Files" matching MCP servers:

Enables MCP clients to extract tables and text from digital PDF invoices, bank statements, and bills into CSV, JSON, or Excel, with automatic PII redaction by default.

Provides deterministic, schema-driven structured data extraction from PDF documents via regex/heuristic matching, enabling repeatable, inspectable, and cost-free field extraction without LLM API calls.

A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.

Enables inspecting local PDFs and extracting tables into CSV, XLSX, or JSON with options for pages, merging, OCR, engine selection, headers, merged cells, regions, and columns.

Enables checking lead rows, CSV files, or Apify datasets for duplicates, email syntax and risk signals, domain issues, missing fields, and stale dates, returning a per-row import, review, or reject verdict so only clean records reach a CRM or sequencer.

Enables document processing with Suparse API, extracting structured data from documents into JSON, CSV, XLSX, or Google Sheets, and supports processing single files or folders.

Enables an AI assistant to reliably read and chunk PDF/text documents, validate extracted JSON against a schema with full error paths, and save structured output—all confined to a single allowed directory.

Enables AI agents to query, send, and manage data from Claro Gerencial SOAP webservices, including listing entities, fetching records, generating FTP files, and submitting XML imports.

Enables AI agents to discover and access 800TB+ of public geospatial data from Source Cooperative, with tools for listing organizations, products, files, and fuzzy search.

Converts PDF, DOCX, PPTX, XLSX, CSV, and JSON into clean, compact, AI-ready Markdown, reducing tokens up to 65%.

Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.

AI-powered data integration platform. Onboard users and run DPF data workflows.

Enables local MCP-assisted processing of Access database tables, HTML5 advertising ZIP image assets, layered PDFs, and ONIX book-update requests through RapidAPI. It saves results in a selected workspace folder while requiring explicit consent for each processing call.

Enables creating and deploying KoboToolbox XLSForm questionnaires, managing data collection, analyzing submissions, and generating Excel, Word, and PDF deliverables directly from a Claude conversation.

Generates formatted Excel (.xlsx) files from user requests and deposits them into Cleyrop project data.

Creates compact skeleton representations of large JSON files by preserving structure while truncating string values and deduplicating arrays, helping users understand JSON structure without processing the full data payload.

Extract structured data from invoices, receipts, purchase orders and bank statements with ParserBee Parser Templates. Also lists templates, checks page credits and fetches recent extractions.

Read-only MCP server for extracting data across multiple CallTrackingMetrics sub-accounts using a single parent API key. Enables cross-account call data, reports, numbers, contacts, and configuration analysis for resellers and agencies via Claude.

Provides a read-only MCP interface for Azure Data Factory monitoring and root-cause analysis, with a health check for MCP clients.

Converts PDF and CSV files to Markdown from AI agents via cloud API, with browser-based Google login and saved convert defaults.

Converts PDF bank statements into structured data (Markdown, JSON, CSV, JSONL) with verified transactions and balance checks, enabling agents to audit numbers.

Turns a folder of CSV, Parquet, and JSON files into a single SQL-queryable source for AI agents, supporting JOINs across files with read-only sandboxed access.

A tutorial implementation MCP server that enables analysis of CSV and Parquet files. Allows users to summarize data and query file information through natural language interactions.

A server providing PDF form manipulation tools via MCP's API, allowing users to find PDFs across directories, extract form field information, and visualize form fields in documents.

Enables document processing through Upstage AI services including parsing various document formats, extracting structured information with custom schemas, auto-generating extraction schemas, and classifying documents into categories.

An open-source MCP server that connects to various data sources (SQL databases, CSV, Parquet files), allowing AI models to execute SQL queries and generate data visualizations for analytics and business intelligence.

The JSON to Excel MCP provides a standardized interface for converting (1)JSON data (2)URL pointing to JSON files into CSV format

An MCP server that enables AI assistants to load, query, and analyze local CSV files using tools for filtering, aggregation, and grouping. It provides capabilities to describe schemas, calculate statistics, and sample data directly from CSV files.

A Model Context Protocol server that enables AI assistants to read from and write to Microsoft Excel files, supporting formats like xlsx, xlsm, xltx, and xltm.

Enables AI assistants to extract and structure content from documents (PDFs, images, Office files) using Upstage AI's document digitization and information extraction APIs.