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

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.

Enables LLMs to execute Python code securely in a sandboxed environment. Supports configurable restrictions like no network access and returns results including files.

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

Execute Python, JavaScript, or SQL code in a sandboxed environment and retrieve stdout, execution time, and errors with pay-per-call via x402 (USDC on Base L2).

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

Model Context Protocol server to run Python code in a sandbox.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Transforms Figma design data into a compact, LLM-friendly format for code generation, reducing size by 99.5% while preserving UI-critical information.

Production-ready MCP server for secure Python code execution with artifact capture, virtual environment support, and LM Studio integration.

Enables AI coding agents to safely execute commands, run tests, and modify project files inside disposable, policy-enforced Docker sandboxes that are isolated from the host machine and its credentials.

Enables running arbitrary JavaScript code in isolated Docker containers with on-demand npm dependency installation, allowing for ephemeral script execution and long-running services with controlled resource limits.

MCP server for ingesting UI screenshots, Figma MCP node JSON, or hybrid Figma-plus-screenshot sources into a cross-platform design-to-code artifact pipeline.

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

Enables you to audit your AI agent skills by running each one against an agent that cannot see it, diffing the resulting artifacts, and grading whether each skill genuinely improves, changes nothing, or worsens the output.

A local, keyless MCP server simulating Forge's industrial telemetry kernel, enabling agents to normalize vendor-specific machine data, forecast breaches, and test integrations against realistic equipment data without credentials or persistence.

A public MCP server providing test fixtures for developers and QA, with a single tool 'identity' that returns a unique canary string to verify the server's response.

A sandbox MCP server for testing and debugging MCP tools and interactions via the MCP Inspector.

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.