"Parsing and Unparsing CSV Files for AI Context Use" 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.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

Enables Claude Cowork on Windows to read, write, edit, list, find, and regex-search files inside a WSL distribution over stdio, accepting Windows and Linux path spellings. Access is confined to server-fixed roots, with secrets files refused, key-shaped strings redacted, and no delete or move operations.

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

A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.

Enables local, private analysis of CSV and TSV files through natural-language agents such as Grok Bot and Cursor, offering file listing, profiling, SQL-like queries, summaries, group-bys, pivot tables, cleaning previews and generated charts. All computation happens on the user's own machine against an allowlisted folder, with no network calls, telemetry or data leaving the host.

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.

Enables ChatGPT/Codex to read, search, and edit files in a single allowed folder on Windows through OpenAI Secure MCP Tunnel.

Stdio MCP server for sandboxed file access — read files, search content, safely edit with checksums, and manage file structure.

Enables LibreChat agents to manage per-user private files, persistent documentation, RAG indexing and semantic search, and publish files via secure opaque public links.

A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.

An MCP server for local testing that enables file management operations, requiring authentication via Microsoft identity platform credentials.

Enables AI agents to safely explore directories, read files, search content by pattern or filename, and edit files with checksum verification and dry-run preview within sandboxed filesystem access.

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

Enables AI assistants to access and inspect local files within a specified sandbox root.

Enables secure, read-only access to local project files (including text, DOCX, PDF, and XLSX) through MCP, with strict directory whitelisting and no write, edit, or command-execution tools.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

Provides safe, allowlisted local filesystem access for MCP-compatible AI clients, enabling directory listing, file reading/writing (with byte limits), and text search while blocking paths outside approved roots and symlink escapes.