"Automating File Processing and Communication Tasks" matching MCP servers:

MCP server for converting between everyday file formats (CSV, Excel, Markdown, Word), including a GxP-compliant Markdown to Word template. Exposes four conversion tools over stdio.

Enables agents to securely stage, validate, and submit binary data for on-premises storage, then list, inspect, process via registered server-side processors, and token-guarded delete those assets using opaque identifiers. Upload bytes travel over a separate data plane rather than through MCP JSON, with staging, validation, and prepare/apply/verify flows enforced throughout.

A FastMCP server for data processing tasks including CSV, JSON, text analysis, and numeric statistics, enabling users to parse, summarise, filter, convert, and analyze data through MCP tools.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

Enables querying ERP data via an external API with adaptive caching, and accessing data from Google Sheets or local Excel/CSV files through dual MCP endpoints.

This read-only MCP Server allows you to connect to CSV Files data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for CSV Files (https://www.cdata.com/drivers/csv/download/mcp).

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Enables AI assistants to interact with security data pipelines and map data to the Open Cybersecurity Schema Framework (OCSF) through Tenzir. Provides seamless integration for processing and analyzing cybersecurity data using natural language.

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

Enables agents to validate climate-processing configurations, inspect sample CSV data, and run a deterministic pipeline that aggregates daily records into monthly summaries and plots, with sandboxed paths and isolated outputs.

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.

Parses NACHA/ACH files into structured JSON and summaries, performing structural and arithmetic validation with IAT support, enabling automated file inspection and validation through MCP clients.

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.

Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.

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.