"CodeQL for Code Auditing" matching MCP servers:

Executes Python code in isolated rootless containers while proxying MCP server tools, reducing context overhead by 95%+ and enabling complex multi-tool workflows through sandboxed code execution.

A lightweight Model Context Protocol (MCP) orchestrator designed for efficiency at scale. It features TOON compression (reducing token usage by 30-90%) and Lazy Loading, making it the ideal solution for complex, multi-tool agentic workflows.

Enables Claude Code to delegate tasks to OpenAI's Codex CLI (GPT-5.4) with structured execution traces, parallel execution, session persistence, and adversarial code review.

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

Offloads expensive code reading, editing, and checking tasks to DeepSeek through Claude Code, saving Codex main-thread tokens by 40-60%.

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

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

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.

Executes TypeScript code in a secure sandbox with IPC-bridged access to MCP tools like filesystem operations and network requests.

Enables AI agents to execute C++ code, test solutions against multiple test cases, analyze performance, and generate test cases using OnlineGDB's online compiler. Perfect for solving competitive programming problems with iterative self-correction capabilities.

Enables safe execution of Python code with AI assistance and integration with Model Context Protocol tools.

A Code Mode MCP server for the e2b API, giving agents three tools (search, execute_read, execute_write) to write and run JavaScript functions inside sandboxed environments for API discovery and calls.

Enables AI agents to write and execute Python code in an isolated sandbox that can orchestrate multiple MCP tool calls, reducing context window bloat and improving efficiency for complex workflows.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

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.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

An MCP server for running Claude Code and the Codex CLI as a pair: Claude drives, and hands self-contained tasks to Codex as background jobs.

Enables AI coding assistants to browse Unreal Python API documentation, search classes and functions, and execute Python code in Unreal Editor.

A server that allows LLMs to run Claude Code with all permissions bypassed automatically, enabling code execution and file editing without permission interruptions.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.