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

Enables coding agents and CI/CD pipelines to audit untrusted code by detecting Python sandbox escapes, SQL injection taint, ReDoS regex vulnerabilities, and CORS misconfigurations, while generating Seccomp BPF filters for safer execution.

Enables AI agents to safely execute Python code and shell commands in an ephemeral, isolated scratchpad with pre-execution AST security checks, timeout enforcement, token-shielded output, and file diff tracking. It also exposes static code-security inspection to flag forbidden imports and reflective escape attempts before execution.

Provides a secure, containerized Python sandbox for executing LLM-generated code with multi-layer isolation, along with JSON/CSV validation and workspace state snapshots.

Enables a sandboxed Claude Code session to see editor selections, review proposed edits as VS Code diffs, and read workspace diagnostics through an MCP-over-WebSocket IDE bridge.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

MCP server for Speakeasy — Windows API emulation for binary analysis. It runs a .exe in a Wine-like sandbox and returns a structured API trace.

truth is a deterministic fact-checker for the claims an AI coding agent makes about its own work.

On-demand micro-mutation sandbox for AI test verification that maps weaknesses in unit tests by running isolated mutation testing via the Model Context Protocol.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

Enables a coding agent to get short, token-efficient answers about a project through grouped searches, focused symbol or section reads, and bounded read-only script output, with safety limits on paths, secrets, commands, and response size.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

MCP server that provides npm package information for AI agents during TypeScript development.

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

MCP server that brings Octopus AI code review into editors, allowing review of code changes and asking questions about your codebase. Integrates with Cursor, Claude, or any MCP client via natural language.

Enables AI agents to search and retrieve details about Odoo code elements (models, fields, views, etc.) with exact file locations using MCP tools.

Enables any general-purpose agent to mod IL2CPP, Mono (.NET), and Unreal games by resolving hook targets from engine metadata rather than memory guessing. Provides 45 tools covering the full workflow of finding a game, indexing types/fields/methods, injecting a Frida probe, hooking methods, and reading or writing game memory.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

Provides coding agents with a compact map of a TypeScript/TSX codebase, enabling direct answers about symbol locations, imports, dependencies, and references while reducing token usage.

Enables the generation and iterative refinement of React UI components from natural language descriptions or design images using Vercel's v0 API. It provides tools for design-to-code workflows and chat-based component development within Claude, Cursor, and other MCP environments.

A mcp server to allow LLMS gain context about shadcn ui component structure,usage and installation

Local-first, code-aware engineering cognition for AI coding agents - persistent memory, contextual retrieval, and continuous cognition about your codebase.

An MCP server that recovers original C# class, method, field, and parameter names from Unity IL2CPP global-metadata.dat files to assist with reverse engineering Unity games.

A Model Context Protocol server that provides clj-kondo linting capabilities for Clojure/ClojureScript/EDN files, useful for environments like Claude code and desktop that lack built-in linting.

Enables local detection of protected health information in source code before it reaches LLM prompts, log statements, or analytics calls.

AI-powered characterization test generator that reads Python functions or class methods, synthesizes inputs, captures behavior in a sandbox, and emits pytest files to lock legacy code behavior for safe refactoring.

Enables coding agents to capture and inspect running projects, resolve real assets from free sources, and check source for design tells, providing an evidence loop for improving websites, games, and motion.

Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.

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.

Allows developers to query security findings (SAST issues, secrets, patches) using natural language within AI-assisted tools like Claude Desktop, Cursor, and other MCP-compatible environments.