"Code Execution" matching MCP servers:

An MCP server that enables AI agents to execute sandboxed JavaScript and TypeScript code instead of calling individual tools directly. It significantly reduces token usage by allowing agents to filter, aggregate, and transform data locally before returning results.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

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.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.

A Python code execution sandbox based on IPython and Docker. Stateful code execution, file transfer between host and container, configurable network access.

An MCP server that lets Claude Code delegate coding tasks such as code generation, review, refactoring, and test writing to a local Ollama instance running a Qwen3 model.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Enables cluster-aware command execution and automatic task routing across distributed nodes based on system load, architecture, and OS requirements. It supports parallel execution, remote node management via SSH, and dynamic load balancing for agentic workflows.

An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.

Enables AI-powered generation of styled QR codes with 10 design presets, supporting single or batch creation with custom logos and formats (SVG/PNG) directly from AI tools.

Enables AI assistants to review GitHub and GitLab pull requests and merge requests, supporting multiple transports and custom review rules.

A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.

A lightweight, configurable server that fetches coding guidelines, security rules, and validation patterns from external sources to help development teams maintain code quality standards in WordPress projects.

Enables AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.

Enables semantic code search across local projects and Git repositories using AI embeddings with ChromaDB. Supports both OpenAI and local Ollama models for private, enterprise-ready code analysis and similar code discovery.

AI-powered code review tool that detects AI-generated code defects invisible to traditional linters — hallucinated packages, deprecated APIs, cross-file contradictions, hidden security anti-patterns, and over-engineering. Works as a standalone CLI, GitHub Action, or MCP server. Supports TypeScript, Python, Java, Go, and Kotlin. Free for individuals, no API key required.

Enables AI assistants to review GitLab merge requests by fetching changes, analyzing diffs, adding comments, and managing approvals through the GitLab API. Supports complete merge request analysis, file-specific reviews, and version comparisons.

Delegates expensive or long-running AI tasks to Kubernetes-hosted Claude agents running on OpenShift. Enables creating, managing, and monitoring remote agentic sessions for complex work like codebase analysis and security audits.

A secure Node.js execution environment that allows coding agents and LLMs to run JavaScript dynamically, install NPM packages, and retrieve results while adhering to the Model Control Protocol.

An MCP server that automates code review by providing syntax checking, code explanation, and improvement suggestions using a multi-agent system.

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.

Integrates GitHub repository management and local file system access to enable AI agents to perform code reviews and manage pull requests. It provides tools for listing repositories, retrieving PR diffs, and searching or reading files within a specified workspace.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

Allows agents to lookup code snippets in your project. Uses a remote MCP server with a collection of code snippets, with support for automatic project language detection.

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.

Enables retrieval of Nebraska Revised Statutes by citation, distinguishing valid statute hits from misses.

Provides deep source code analysis for Unreal Engine codebases, allowing AI assistants to understand C++ class structures, search code, and analyze subsystems.