"Damn Vulnerable MCP" matching MCP servers:

An educational project that deliberately implements vulnerable MCP servers to demonstrate various security risks like prompt injection, tool poisoning, and code execution for training security researchers and AI safety professionals.

A vulnerable MCP server implementation that demonstrates how poor coding practices can lead to security issues like Remote Code Execution, designed for educational purposes to add numbers.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

Ephemeral MicroVM-isolated code execution for AI agents. Run Python, Node, or bash — fresh hardware-isolated VM per call, hard-purged after. No state persists between calls.

Allows LLMs to execute Wolfram Language code in a secure, session-based environment by providing an interface to interact with a Wolfram Mathematica kernel.

MCP server that gives AI assistants a secure gVisor-isolated sandbox to run Python or JavaScript code, returning stdout, stderr, and exit codes without local access.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

A code-execution MCP server for Klaviyo and Shopify analytics, enabling safe JavaScript execution in a V8 sandbox with state persistence across calls.

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

Enables AI assistants to run code in 24 programming languages on HackerEarth's sandboxed servers and read the printed output or errors, without installing local toolchains. It also lists supported languages with exact identifiers for use when submitting code.

Enables MCP-compatible AI assistants to run Python code on Google Colab GPU/TPU runtimes, supporting accelerators like T4, A100, H100, with background execution and Google Drive integration.

An MCP bridge that lets Codex supervise Reasonix as an implementation worker in an isolated Git worktree, ensuring safe delegation with scoped writes and sandboxed execution.

MCP server for Archicad automation, enabling AI assistants to run Python scripts against running Archicad instances via the Tapir JSON API for complex workflows.

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.

Enables AI agents to interact with Jupyter notebooks via MCP tools for querying, modifying, executing, and setting up notebooks, with state preservation and real-time collaboration.

Enables MCP clients to execute Python code directly via stdin, preserving quotes, f-strings, and backslashes exactly as written, and returns stdout, stderr, and exit codes.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Lets AI assistants use MetaModel's formula engine for certified computation, turning published calculators, pricing tools, and engineering models into AI-callable tools with no hallucinated math.

An MCP server for running Claude Code and the Codex CLI as a pair: Claude drives, and hands self-contained tasks to Codex as background jobs.