"GitHub repository operations: reading files, editing structure, and extracting data" matching MCP servers:

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

A server that allows AI assistants to browse and read files from specified GitHub repositories, providing access to repository contents via the Model Context Protocol.

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.

Enables AI agents to perform exact-match, transactional multi-file edits with atomic writes, dry-run diffs, and self-correcting error diagnostics that reduce token usage.

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

A local MCP server that gives Claude a durable reading room for EPUB and plain text books, enabling chunk-by-chunk navigation, annotations, progress tracking, and shared margin cards.

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

Enables comprehensive Windows system management through Claude Desktop, including PowerShell/CMD execution, file operations, archive handling, Git tools, network testing, and system monitoring. Provides a complete toolkit for Windows automation and administration tasks.

A Model Context Protocol server that enables enhanced file system operations including reading, writing, copying, moving files with streaming capabilities, directory management, file watching, and change tracking.

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

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

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.

MCP Server for the GitHub API, enabling file operations, repository management, search functionality, and more.

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.

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.

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。

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

Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

Enables read-only MCP access to an unpacked game data directory, supporting directory listing, paginated text/XML reading, content search, translation lookup, and retrieval of spell/entity definitions without executing Lua or computing derived values.

Provides a secure, constrained filesystem workspace for LLM agents to manage files, notes, and code artifacts via stdio or remote HTTP. It features granular access controls, including extension whitelisting, storage quotas, and immutable paths for safe automated file operations.

A Model Context Protocol server that gives AI agents bounded, auditable access to propose changes to an Obsidian vault stored in GitHub, with per-agent expiring tokens, read/write/deny path policies, mutability rules, frontmatter checks, and human-reviewed proposal branches.

Provides safe local file operations through MCP, including reading, writing, searching, organizing, and protected deletion with configurable path restrictions.

A comprehensive MCP server that enables AI models to perform local file operations, command execution, and task management across multiple platforms. It features advanced capabilities like row-level file editing, directory searching, and system monitoring with built-in security filters.

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

MCP server for privacy-gated local Apple data access including Mail, Messages, Notes, Calendar, Contacts, Photos, Reminders, Voice Memos, and iCloud Drive.

Profiles authorized local datasets into inspectable Data Context for AI assistants, with optional local model-assisted interpretation.

Connects compatible AI clients to registered Windows or macOS computers, allowing users to inspect systems, work with files, run supported commands, and automate workflows through authorized remote access.

Enables an AI host to list, read, and move files within a single designated folder, where each action is held until a human approves it through a consent card and the decision is recorded on a tamper-evident chain. Actions proceed only with a written receipt, and any missing answer or error counts as a refusal.