"Managing an AWS Environment" matching MCP servers:

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables running Jupyter notebooks on temporary AWS compute (EC2 + SSM) with cost estimation, dry-run planning, progress reporting, and automatic cleanup.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with AWS S3 Control API through natural language, auto-generated using AG2's MCP builder.

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 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.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

An MCP server that manages an IPython kernel, allowing LLMs to execute Python code in a project's virtual environment.

A bridge server that provides access to an Odoo shell environment, allowing execution of Python code within an Odoo database context for model introspection and database operations.

Manages a Neo4j knowledge graph of reusable Python functions, documentation, and environment variables, enabling dynamic script composition and execution with automatic dependency management and secret protection.

Remote-control Unity Editor from any AI IDE via file-based IPC — 62 tools, zero dependencies

Runs AI-generated code in secure Firecracker microVMs with opt-in network policy enforcement, PII scanning, prompt injection defense, and audit logging. Exposes MCP tools for running commands, managing files, and the full sandbox lifecycle.

A Model Context Protocol server that enables interaction with PostgreSQL databases for analyzing setups, debugging issues, managing schemas, migrating data, and monitoring performance.

Provides a sandboxed Docker environment for executing Python code against API endpoints, exposing tools for discovery, inspection, execution, and reuse.

Enables coding agents to build, test, archive, and run iOS apps on a remote Mac fleet from any environment, with XcodeBuildMCP-compatible tools and live simulator access.

A demonstration server that reveals security risks by accessing sensitive environment variables, illustrating how MCP tools can potentially leak user data without explicit consent.

Enables AI agents to create, modify, and deploy web projects through the AICre8 platform's sandbox environment. It supports project management, code generation, and direct shell command execution for streamlined web development.

Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.

Provides AI assistants with live access to a Gerbil Scheme environment to evaluate expressions, look up module exports, and check syntax. It enables real-time interaction with the gxi runtime for macro expansion and symbol searching.

MCP server for Dameng database, providing tools to test connection, list tables, count tables, and execute SQL via environment variables.