"Tools for Testing in Python and Java" matching MCP servers:

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

A full-featured secure MCP server for local file system operations, with built-in image processing, OCR and media tools.

Enables LLMs to run Python code and scripts across system and conda environments, list and install packages, and read or write text and binary files within an isolated working directory. It also provides prompt templates for generating, refactoring, and debugging Python code.

Enables LLMs to manage Python environments, execute Python code and scripts, install packages, and read or write files securely within a configured working directory.

Enables LLMs to execute Python code and scripts, manage Python environments and packages, and read or write files within an isolated working directory. It also provides prompt templates for common Python tasks such as function creation, refactoring, and debugging.

Enables LLMs to run Python code and scripts, manage Python environments and packages, and read or write files within an isolated working directory. It also provides prompts for common Python tasks such as function creation, refactoring, and debugging.

Enables LLMs to manage Python environments and packages, execute Python code or scripts, and read or write files within a secured working directory. It also provides prompts for common Python tasks such as function creation, refactoring, and debugging.

Enables LLMs to run Python code and scripts across available environments, manage packages, and read/write files within a secured working directory. It also provides prompts and resources for common Python development tasks.

Enables LLMs to execute Python code and scripts across system and conda environments, manage installed packages, and read or write text and binary files within an isolated working directory. It also exposes prompts for generating, refactoring, and debugging Python code.

Enables LLMs to manage Python environments, execute Python code and scripts, install packages, and read or write files within an isolated working directory.

Enables LLMs to execute Python code and scripts across system and conda environments, manage installed packages, and read or write text and binary files within an isolated working directory. It also exposes environment, package, and file resources plus prompt templates for creating, refactoring, and debugging Python code.

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 coding agents to browse chats, read and search messages, look up contacts, save received files, and send messages or files through a linked account.

A Python MCP server that generates complete Vue 3 CRUD structures with Composition API, including components, services, stores, and routes.

Enables extraction of recipes from PDFs or JPG files and conversion into structured HTML, with interactive region selection and OCR via a web GUI.

An MCP server that exposes macOS Spotlight search as tools, wrapping mdfind and mdls to provide full-text and metadata file search across the system.

Enables LLMs to interact with Python environments, execute code, manage files, and handle packages through the Model Context Protocol.

Enables agents to compress JPEG, PNG, and WebP images to a target byte size, split PDFs by page or ranges, and remove image metadata while processing local files without sending file bytes over the network.

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.

A secure, read-only MCP server for browsing and searching files in a specified directory with path traversal protection and .gitignore support.

A full-featured secure MCP server for local file system operations, with built-in image processing, OCR and media tools. Fully compliant with the official Model Context Protocol specification, offering standardized request/response schemas, large-file streaming I/O, multi-transport remote deployment, and comprehensive text search & replace functionality for LLM agent integration.

Enterprise-grade MCP server integrating Claude AI capabilities, enabling AI-powered conversations, file operations, and system tools via the Model Context Protocol.

An MCP server for reading, writing, and analyzing Excel files using Python, pandas, and openpyxl. It enables tasks such as managing multiple worksheets, performing structural data analysis, and creating new files from JSON data.

A native Nextcloud app that exposes the instance as an MCP server so Claude and other MCP clients can read, search, and (with admin-granted permissions) edit files, notes, calendars, Deck cards, and Talk conversations. It runs inside Nextcloud with OAuth or app-password sign-in, applying each user's own Nextcloud permissions and admin-controlled per-operation grants.

The local PDF workflow for Claude Desktop and MCP hosts: fill, sign, merge, split, extract, and analyze PDFs without sending files to a web app.

A collection of small MCP servers for macOS automation that expose Apple Mail, MoneyMoney, and Spotlight functionality as tools via AppleScript and command-line, enabling AI applications to search mail, manage contacts and transactions, and perform system-wide file searches through natural language.

A secure MCP server enabling read-only access and file search capabilities within a specified directory, while respecting .gitignore patterns.

Enables coding agents to read Telegram chats and messages, manage mirrored chats, send messages, and save or send files on the user's own account.

Enables LLMs to manage Python environments, execute code and scripts, install packages, and read or write files within an isolated working directory.

Enables LLMs to interact with Python environments, run code and scripts, manage packages, and read or write files within a configured working directory.

An MCP server that converts and processes document formats such as DOCX and PDF into Markdown, enabling AI assistants to work with document contents.

Enables LLMs to interact with local Python environments, execute code and scripts, manage packages, and read or write files within an isolated working directory.

Enables LLMs to interact with Python environments, execute code and scripts, manage packages, and read or write files within an isolated working directory.

Enables LLMs to interact with Python environments, execute code or scripts, manage packages, and read/write files within an isolated working directory.

Enables LLMs to execute Python code and scripts across system and conda environments, manage installed packages, and read or write text and binary files within an isolated working directory.

Enables LLMs to work with local Python environments by listing environments and installed packages, installing dependencies, and running code or scripts. Also supports reading, writing, and listing files within a sandboxed working directory.

Enables LLMs to interact with Python environments, execute code, manage packages, and perform file operations within a configurable working directory.

Enables LLMs to interact with Python environments, execute code or scripts, manage packages, and read/write files within an isolated working directory.

Enables LLMs to inspect and use Python environments, execute code or scripts, manage installed packages, and read or write files within an isolated working directory.

Enables LLMs to manage Python environments, execute code and scripts, install packages, and read/write files within an isolated working directory. It also provides prompts for common tasks such as function creation, refactoring, and debugging.