"Evaluating an Expo Go App and Associated React Native Code in an Android Emulator" matching MCP servers:

Provides comprehensive tools for React Native development, automating project initialization, version management, upgrades, Expo integration, and development workflows through AI assistance.

Enables execution of Go code in the Go Playground sandbox and generation of shareable URLs for code snippets. Provides tools to run Go code, share code via URLs, or perform both operations simultaneously.

Converts Figma designs to React Native components, allowing users to extract components from Figma designs and generate corresponding React Native components with proper typing and styling.

Enables AI agents to act as local Android developers with compilation, emulator, asset management, and diagnostics capabilities for a closed-loop build cycle.

Wraps OpenAI's Codex CLI as an MCP server, enabling AI clients like KiloCode, Roo Code, and Cline to leverage Codex for code generation, debugging, and analysis through natural language.

Persistent memory and pattern learning for AI coding assistants via MCP.

what is go-mcp-postgres? go-mcp-postgres is a Model Context Protocol (MCP) server designed for interacting with Postgres databases, allowing for easy CRUD operations and automation without the need for a Node.js or Python environment.

react-mcp integrates with Claude Desktop, enabling the creation and modification of React apps based on user prompts

A proxy server that allows LLM clients to use Databutton app API endpoints as tools through the MCP protocol over websockets.

Enables AI-powered video creation by writing React/Remotion code, compiling it in real-time, and rendering the result as a live video inline in the chat.

Enables AI-powered video creation by letting the model write React/Remotion code, compiling it in real-time, and rendering the video inline in the chat interface via an interactive widget.

Enables a model to write short Python programs that call a wrapped MCP server's tools as async functions, rather than invoking them one at a time. The program runs in a locked-down Docker sandbox, and every tool call passes through a host-side bridge that enforces an allowlist, schema-validated arguments, call budgets, timeouts and output caps.

Enables AI agents to run untrusted, model-generated Python code in a locked-down throwaway Docker container with enforced isolation and resource limits. Supports starting, checking, and stopping asynchronous runs while returning structured status reports without exposing the host, network, or Docker controls.

An MCP server that implements Claude Code-like functionality, allowing the AI to analyze codebases, modify files, execute commands, and manage projects through direct file system interactions.

MCP server for E2B code sandbox, enabling creation, management, and execution of code in secure sandboxes using Python and shell commands.

An MCP server that gives orchestrator agents fine-grained control over interactive Claude Code sessions running inside tmux, enabling mid-session steering, interruption, and token-efficient result extraction.

An enhanced Model Context Protocol (MCP) server that allows running Claude Code in one-shot mode with permissions bypassed automatically, featuring advanced task

An MCP server that provides code review functionality using OpenAI, Google, and Anthropic models, serving as a "second opinion" tool that works with any MCP client.

A MCP server for managing and storing code snippets in various programming languages, allowing users to create, list, and delete snippets via a standardized interface.

A Model Context Protocol server that helps large language models process code repositories by providing file tree generation, code merging, and code analysis capabilities.

An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.

This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically

An MCP server that enables AI agents to execute terminal commands and Python code on the host system, leveraging Agent Zero's battle-tested implementation with session management and smart output handling.

Provides tools for AI-driven development workflows including file system operations, code analysis, code execution, web fetching, and search.

Enables running user-supplied scripts inside resource-limited, network-isolated Docker containers built from human-reviewed Dockerfiles, with jobs driven by an outbound-only worker.

An MCP server that allows Claude Desktop to remotely control Claude Code instances for executing commands and managing files.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

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.

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).

Turns any OpenAPI spec into two sandboxed tools, search and execute, so an AI agent can discover endpoints and run small JavaScript programs against an entire API using under 1,000 tokens of context. Requests are read-only by default and the API key never enters the sandbox.