"A platform for managing infrastructure as code with Terraform Cloud" 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.

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.

The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug

An MCP server that integrates AI assistants like Claude with GitLab's merge requests, allowing them to review code changes, add comments, and approve/unapprove merge requests directly through the GitLab API.

MCP server for the Agent Platform API, enabling management of sandbox environments through MCP protocol. Exposes tools to interact with sandbox lifecycle operations such as start, stop, and status checks.

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.

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

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

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.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Creates short-lived, offline JavaScript sandbox containers for safe code execution via MCP, with no network access and strict resource limits.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

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.

🗂️ A Model Context Protocol (MCP) server that provides integration with Turso databases for LLMs. This server implements a two-level authentication system to handle both organization-level and database-level operations, making it easy to manage and query Turso databases directly from LLMs.

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

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

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.

Enables secure cloud-based execution of code across 14+ programming languages within a sandboxed environment. It supports file management, standard input/output handling, and automatic generation of visual artifacts like plots and charts.

Enables AI clients to securely operate isolated coding workspaces with file, command, Git, and deployment tools via authenticated remote MCP.

Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.

Wraps Claude Code as a server using the Model Context Protocol (MCP), allowing teams to interact with Claude Code through a Slack bot interface.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Enables Codex to offload expensive code reading, editing, and checking to a worker agent via Claude Code, supporting async jobs and long-running tasks.

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.

Enables AI assistants to interact with VS Code for language intelligence, debugging, and code execution.

This server gives AI clients a persistent, isolated Linux container in which the model can run any bash command as root with internet access, install packages and start long-running processes without command filtering. Files produced inside it can be handed back to the user as signed, expiring public download links suitable for PDFs, images, audio and video.