"Information about sandbox environments or games" matching MCP servers:

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

Enables AI agents to extract, sync, test, and debug Roblox games bidirectionally between Studio and filesystem via MCP.

Enables delegating coding tasks to sandboxed agents, returning changes as auditable diffs for human review before applying or discarding them.

Provides MCP tools to create, run commands in, checkpoint, and delete durable cloud environments, giving coding agents persistent state between calls.

A stdio MCP server that lets Claude Code delegate coding tasks to an OpenCode instance (optionally attached to an internal LLM gateway), with follow-up replies, status polling, output/diff retrieval, cancellation, and cleanup handled in a single session. It supports managed or attach modes, sandbox and approval policies, parallel fan-out delegations, and read-only review workflows.

Enables AI agents to perform software engineering tasks inside an isolated, deterministic sandbox—exploring repositories, reproducing failures, applying patches, running tests, and verifying solutions against hidden suites through MCP tools.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

Enables external agents to list T3 environments and projects, start coding threads, monitor progress, send follow-up instructions, and interrupt running turns via MCP.

Bridges the OpenAI Codex CLI app-server to MCP clients, letting agents launch and resume Codex coding sessions within a chosen workspace under configurable sandbox and approval policies. It exposes tools for sending prompts, long-polling task progress and live command output, approving or canceling runtime requests, and listing or reading past session history.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

Runs as an MCP server providing file system operations, shell execution, and system information tools, allowing Claude or any MCP client to edit files and control the machine.

Enables direct MCP-based pairing with T3 Code environments, allowing users to manage environments and projects, start and continue turns, and inspect thread history over stdio without requiring T3 Connect or a local turn CLI.

A personal AI coding assistant that connects to various development environments and helps automate tasks, provide codebase insights, and improve coding decisions by leveraging the Model Context Protocol.

Agentic MCP server that receives a feature specification from an IDE, autonomously implements it in an isolated sandbox via an internal loop (plan-act-validate-correct), and returns a structured report with diffs and test results, without modifying the original repository.

Lets AI coding agents ask a Rails app about itself: 35 read-only tools answer from the schema, models, routes, controllers, views, jobs and conventions, over MCP or the command line, even when the app cannot boot.

An MCP server for local Cocos Creator 3.8 automation, enabling coding agents to create projects, edit scenes, and build WeChat Mini Games directly on a developer machine.

Connects AI assistants to a local Codex engine for performing deep, project-level code reviews and automated refactoring. It enables context-aware bug fixes and multi-file analysis through a standardized bridge between modern AI clients and local development environments.

An MCP server for automating Google Jules that enables seamless integration for task creation, code analysis, and AI-powered development workflows. It supports multiple session modes including Browserbase and cookie-based authentication for both local and cloud environments.

Enables launching and supervising local Codex and Claude Code agent sessions and one-shot tasks, exposing run, list, stop, and output operations over MCP with session-scoped permissions and sandbox controls.

Enables bounded, local coding tasks to be delegated to OpenAI-compatible models with explicit working directory and read/write paths, pre-application unified-diff validation, and optional verification commands. It routes tasks by complexity and risk, while blocking sensitive changes such as auth, payment, secrets, migrations, database, deployment, or production environments.

A semantic context compiler MCP server that provides stratified L0-L3 code context with exact-source escalation, enabling project analysis, symbol contracts, exact source retrieval, and a patching workflow with sandbox validation.

Enables AI agents to autonomously develop and test Godot 4 games through an MCP-based feedback loop, providing tools for authoring, running, observing, playtesting, and verifying game projects.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

Enables external AI clients to invoke an autonomous coding agent that plans, fixes, and self-corrects code in an isolated Docker sandbox via run_task and run_tests tools.

Enables AI agents to build games with the Cocos4 engine by providing high-level scaffolding tools and transparently proxying native MCP tools.

Enables two-way collaboration between Claude Code and the Codex CLI: Claude can hand off plans for execution or adversarial review, while the working agent can block to ask Claude questions, report progress or findings, and receive mid-run corrections. Supports multiple named, resumable sessions per project with configurable model, effort, and sandbox settings.

A coordination layer for coding agents that provides identities, message threading, and searchable history. It features file reservation leases to prevent agents from overwriting each other's work in multi-agent environments.

Enables users to run shell commands with compressed output, extract information from large files, drive local opencode and Codex agents, perform browser-automation tasks, and monitor runs via a live dashboard.

Enables coding agents to query a parsed graph of a repository and to recall what earlier sessions learned about it, both stored in FalkorDB behind one traversal. It exposes eight MCP tools over stdio for locating symbols, tracing calls and impact paths, and writing or recalling user- and repo-scoped facts, procedures, and handoffs.

A production MCP integration that lets AI agents control Roblox Studio to autonomously build, test, and debug Roblox games. Provides 39 tools for explorer control, script management, terrain generation, and autonomous testing.