"GitLab操作的MCP服务器" matching MCP servers:

非官方印象笔记MCP服务器，支持笔记本、原生超级笔记、原始ENML和资源附件操作。

A tuned filesystem MCP server for Codex-style development, offering fast file operations, bounded output, and safe edits.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

基于WizTree的磁盘分析MCP服务器，通过MCP工具扫描驱动器、查询磁盘使用情况、搜索路径、比较快照以及可视化文件系统数据。

Provides direct, unsandboxed local machine access via filesystem, Python, Node.js, and shell commands for MCP agents.

A local-first MCP server that handles daily work tasks through your AI assistant: converts meeting notes into todos, manages todo lifecycle, tracks work hours, generates daily/weekly reports, organizes files via move-only operations, and diagnoses dev environments, all guarded by a human-maintained preview/apply safety model.

Z-CLI provides NAS operations like file management, pool queries, search, and file operations through CLI and MCP Server, enabling AI assistants to interact with zspace private cloud.

轻量级跨平台 SSH MCP 服务器，复用本地 SSH 配置实现远程命令执行、文件传输和主机管理。

Enables triage, installation validation, and controlled automation of X-Ways Forensics and related tools through structured MCP tools for agents.

Enables LLM clients to safely perform file operations such as create, read, edit, delete, move, copy, and more, with every path checked against an explicit permission database managed through a desktop GUI.

一组面向coding agent的MCP服务器，用于在SSH主机和WSL发行版中运行命令、管理任务，并以适合模型使用的方式读写远程文件。

自托管的MCP服务器，在Docker沙箱中提供命令执行、后台长任务、大文件传输和多沙箱自动管理，专为AI助手设计。

Enables agents to read, analyze, and edit Google Docs, Sheets, Drive files, and local folders with previews, rollback, and clarification, while supporting MCP clients, local models, and API-key-based models.

Stores and retrieves personal information fields securely, allowing Claude to access your name, address, email, and professional details without re-typing them.

Enables AI assistants to read, edit, and execute Jupyter notebook files (.ipynb) with live kernel output, without requiring JupyterLab.

Analyzes unstructured documents in a local folder, extracting structure and key terms, and supports generating summaries via a host LLM with validated, approval-based report saving.

Enables agents to run read-only coverage and staleness checks on local folders and documents, reporting missing periods or mismatched figures without writes, deletes, or network calls.

An MCP server for reading, rendering, and searching PDF files, specifically optimized for LLMs to extract text, tables, and technical diagrams. It enables metadata retrieval, multi-format text extraction, and page-to-image rendering using PyMuPDF.

locidx

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.