"Code Execution" matching MCP servers:

Scaffolds new MCP servers for the OpenSIN-Code ecosystem with templates for Python, Node, Go; provides tools to add tools, test, validate, register, publish, and audit servers.

Enables Codex CLI to perform code reviews on uncommitted changes via an MCP tool, keeping review context separate from the main session.

A code review MCP server built on FastMCP, supporting security audit, style check, complexity analysis, and bug pattern detection for Python code.

MCP server providing code review, auto-fix, test running, linting, formatting, and refactor suggestions for Claude Code.

Provides comprehensive code analysis through three MCP servers: static analysis for code quality and security, dependency analysis for package management and vulnerabilities, and complexity analysis for maintainability assessment across multiple programming languages.

MCP server for automated code review using AI agents. It analyzes code diffs or file paths for bugs, security issues, and style violations.

Local MCP server for Cursor that analyzes code, finds bugs, generates tests and documentation via OpenRouter.

Enables AI agents to submit code snippets for review and receive structured quality reports covering correctness, security, performance, maintainability, and best practices.

Autonomous AppSec & DAST code and website security scanner across 12 security domains (260+ controls) with 3-Layer Triage.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

A Model Context Protocol (MCP) server for interacting with SonarQube code quality platform.

MCP server for Allure TestOps — lets an LLM agent (Claude Code, Cursor, Windsurf, etc.) inspect test quality without leaving the chat.

Lets an AI assistant statically scan HTML and JavaScript landing-page code that turns Meta's fbclid URL parameter into the _fbc cookie (and hand-written _fbp cookies), flagging known ways the click ID is changed, truncated, or kept from an older ad, without executing the code or contacting Meta.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

Enables coding agents to gate code modifications behind an evidence check, preventing unnecessary edits by requiring reproduction of the problem before allowing changes.

Give AI agents 10 offline tools for market observations, repeated headlines, forecast evaluation, correlation risk and statistical checks. Preserve source clocks, missing data and stated assumptions. Python, CLI and MCP share the same zero-dependency core; no feed collection or trade execution.

Enables independent, read-only adversarial review of candidate test cases and bug findings, returning a review delta that authoring agents reconcile before writing final artifacts.

Local-first data quality validation for Excel/CSV: schema-aware checks with 10 zero-code constraint types (uniqueness, ranges, foreign keys and more) and row-level error reports.

Enables developers to diagnose why FSE 2.0 CDA2 documents are rejected by validating locally, explaining schematron/XSD errors, looking up code systems, and generating synthetic sample documents.

Enables AI coding agents to build and audit Garry's Mod GLua addons with source-aware search, static linting, net security vulnerability scanning, performance profiling, and headless testing.

Provides an isolated workspace for testing candidate code, runs tests, and returns deterministic pass/fail verdicts. Enables automated grading of software engineering solutions by ensuring reproducible test runs.

MCP server for semi-manual QA test execution on real Smart TVs (Tizen/webOS) and local Chrome via Chrome DevTools Protocol, enabling remote control, state inspection, and profiling.

Diffgate MCP server acts as a code review engine, enabling AI coding agents to analyze and validate code diffs before application. It enhances AI workflows by providing self-checking capabilities to optimise and secure code changes.

A ruthless, read-only code review MCP server that analyzes code produced by AI coding assistants, catching missing requirements, security vulnerabilities, edge cases, and performance issues without ever modifying files.

Enables real-time code analysis for JavaScript, TypeScript, and Python through Claude Desktop and other MCP clients, detecting bugs, code smells, and security vulnerabilities with automated quick fixes.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.

Enables an editor LLM to run only preconfigured lint, test, and read-only git commands, blocking arbitrary bash execution.

The pixel-diff verifier for Figma-to-code: converts a frame to HTML, React, Next.js or Tailwind with design tokens, then renders it and pixel-diffs it against Figma until it converges. Also verifies your own running app.

Browser control for Claude Code, on Firefox.

Detects tests that pass no matter what the code does, revealing vacuous tests that provide false confidence in coverage.