"A sandbox environment to run Python code and install dependencies" matching MCP servers:

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.

Enables AI agents to control NetEase Cloud Music playback, login, search, and get personalized recommendations through official APIs.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

A Model Context Protocol server built with FastMCP that provides tools for retrieving the current local date and time. It allows LLMs to access precise temporal information directly from the host environment.

MCP server for the Oanda v20 REST API enabling forex/CFD trading account management, market data retrieval, and order/trade operations with a read-first design and practice environment by default.

MCP server that bridges AI coding assistants to Vibe Kanban, enabling task, session, and queue management without leaving the coding environment.

MCP server exposing TASIE's autonomous SAST, live exploit, and human-gated remediation as tools, enabling ChatGPT clients to scan code, dependencies, and frameworks and receive proof-carrying fixes.

Enables AI assistants to perform governed risk assessments through AIR: discover projects, upload evidence, run assessments, and retrieve structured reports.

An MCP server that enables LLMs to execute Python code on GPU-accelerated compute nodes within SLURM-managed HPC environments. It bridges local clients to remote clusters by launching JupyterLab sessions via SLURM jobs to facilitate high-performance notebook-based computation.

A Model Context Protocol server that provides programmatic APIs for running mutation tests with mutmut, analyzing results, and improving test coverage in Python projects.

Enables LLM clients to inspect local development environment, including Docker container health, pnpm workspace integrity, and stuck process diagnosis.

A Python MCP server that provides language models full read/write access to a Node-RED instance through its Admin HTTP API, enabling flow management with structured Pydantic responses and incremental patching.

A Model Context Protocol server framework featuring dynamic tool loading and automatic tool discovery from a dedicated directory. It leverages FastMCP to provide a robust environment for building, configuring, and testing individual Python-based tools.

A Python MCP server that allows programmatic interaction to find torrents programmatically on YggTorrent and La Cale.

A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.

A Python MCP server that queries Spanish Cadastre services for non-protected cadastral data and exports parcel geometry in GML, GeoJSON, and IFC formats.

An MCP server that bridges local AI agents to Google Colab notebooks, enabling execution of Python code and interaction with notebook states directly from the agent.