"Information about CSV (Comma-Separated Values)" matching MCP servers:

A stdio MCP server for safely reading, analyzing, validating, and transforming CSV/TSV files, with sandboxed file system access and configurable parsing options.

A local MCP server for analyzing CSV files from your filesystem, particularly suited for chatbot conversation logs. Allows listing, reading, filtering, merging, and statistical analysis of CSV data via natural language.

Enables comprehensive CSV file management including creating, editing, analyzing, and transforming CSV data anywhere in the filesystem. Provides statistical analysis, data validation, filtering, and grouping capabilities through MCP protocol over stdio transport.

Enables validating CSV structure, checking simple schemas, converting between CSV and JSON, sampling rows, and finding duplicate keys on local files. All processing stays local, so no user data is ever uploaded.

A Model Context Protocol server for exploring and analyzing CSV files, providing tools for inspection, sampling, schema inference, statistics, filtering, and more.

Manages LinkedIn prospecting CSV files with deduplication and search, reducing LLM token usage by offloading file operations.

Enables Claude to directly access, query, and analyze local CSV files using natural language, keeping data private and local.

Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.

Enables coding agents to extract verbatim, intent-relevant spans from large low-density files like logs, CSV, JSON, and HTML, verified against the original file to reduce context usage.

Enables read-only SQL querying and exploration of data files (CSV, Parquet, JSON, Excel, etc.) via DuckDB, supporting local paths, globs, URLs, and S3 buckets.

MCP server for seamless document format conversion using Pandoc, supporting Markdown, HTML, PDF, DOCX (.docx), csv and more.

Anonymizes documents via the Stript desktop app locally, ensuring personal data never enters the conversation. Provides tools to anonymize files and clipboard content, fetch results, and restore original values to local files.

Convert technical-drawing PDFs and engineering callouts between metric and imperial — values stamped in place, threads cross-referenced, shop-floor rounding.

Provides AI agents with local file-processing capabilities for token counting, RAG chunking, CSV/JSON conversion, QR generation, and more, while keeping documents private on the user's machine.

Enables reading and extracting text from local documents (PDF, Word, Excel, PowerPoint, HWP, Markdown, CSV, etc.) without network access, and provides approval-gated summary saving and file organization.

Enables exporting data from databases to files (CSV, TSV, JSON, BSON, Parquet, XLSX, Binary) with optional cloud storage targets, via a two-step preview-execute safety process.

Go MCP server for multi-format document access — PDF, TXT, MD, DOCX, CSV, images. 12 tools including OCR, search, table extraction, and URL fetch. Single binary, no runtime.

Data-first MCP server for reading and writing spreadsheets (.xlsx, .csv, .ods) - cell-level ops + DuckDB SQL engine.

Enables parsing German bank statement PDFs into structured, validated transaction data, exporting all transactions as German-style CSV, and verifying statement totals via proof calculations, all locally within MCP-compatible clients.

Enables AI assistants to read and write local Excel and CSV files, supporting editing, styling, and image insertion.