"CodeQL for Code Auditing" matching MCP servers:

Enables auditing codebases for production readiness, including linting, testing, CI/CD, security, branch conventions, architecture, and an A–F quality scorecard via MCP tools.

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MCP server for IBM Code Engine — build, push, and deploy containers from Cursor, Copilot, Claude, and Cline using natural language.

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.

An MCP server for managing Modal — apps, containers, volumes, and secrets — and for deploying & running Modal apps directly from Claude Code and other MCP clients.

Local MCP runtime that gives persistent cross-session memory to 12 AI coding agents (Claude Code, Cursor, Codex, Gemini CLI, Windsurf, Amp, and more). SQLite-backed state survives context resets. Install: npm install -g @egchq/egc

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

Provides disposable email inboxes for AI agents to automatically receive and extract OTPs and magic links, enabling seamless email verification during autonomous workflows.

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 Model Context Protocol server that monitors shadow-cljs builds and provides real-time build status updates for ClojureScript projects, allowing LLMs to verify build status after making code changes.

Enables code-review gating by converting a git diff into a typed verdict with safety probabilities, severity, and recommended actions for auto-merge or human review.

Turns Claude Code into an interactive OpenWiFi triage assistant, providing tools for searching Linux wireless patches, Jira tickets, running LLM-based triage, backporting, and building OpenWiFi.

Enables AI coding agents to retrieve the latest stable versions of packages and tools across multiple ecosystems, preventing outdated dependency versions in generated code.

Scan codebases for LLM API calls and estimate monthly costs. Compare costs between git refs to catch cost regressions during code review.

Enables AI agents to query summit registration and forum analytics, review code changes for risks, run fixed quality gates, and perform audited, permission-controlled commits and deployments with minimal access and human approval.

Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your real database schema, it writes code that fails in production. LintBase acts as the bridge. It connects directly to your database, reads the ground truth of your live documents, and generates structured context optimized for AI. 🤖 Stops AI

MCP server for Xcode build optimization, providing build-timing analysis, DerivedData/module-cache management, and build-speed config linting for AI coding agents.

Lightweight Node.js dependency vulnerability audit tool with CLI and MCP Server modes. Supports npm/pnpm, full dependency chain tracing, remote GitHub repo auditing, and generates Markdown/HTML reports.

MCP server that lets coding agents test AI agents. Create YAML test cases, snapshot golden baselines, check for regressions, and generate visual reports all from inside Claude Code or any MCP-compatible tool. Works with LangGraph, CrewAI, OpenAI, Claude, Mistral, and any HTTP API.

This MCP server enables users to manage Codemagic CI/CD builds directly from Claude Code, including listing apps, triggering builds, checking status, and canceling builds.

Enables coding agents and CI/CD pipelines to audit untrusted code by detecting Python sandbox escapes, SQL injection taint, ReDoS regex vulnerabilities, and CORS misconfigurations, while generating Seccomp BPF filters for safer execution.

Post-quantum readiness for AI coding agents: scans code for quantum-vulnerable cryptography (RSA/ECDH/ECDSA/DH) and returns NIST ML-KEM/ML-DSA/SLH-DSA (and hybrid) migration guidance, with fix verification and dependency checks. Content-based, advisory tools only; runs local (npx @quantakrypto/mcp) or as a hosted OAuth endpoint.

MCP server that analyzes GitHub Actions workflow performance, audits configuration for optimization, and provides billing and cache usage insights.

Scaffold and audit Starter Series projects — MCP server, Claude Code skill, and CLI in one package.

Enables AI coding agents to verify code against YAML specifications, detecting missing fields, extra fields, and type mismatches to prevent silent drift before commits.

Enables LLMs to manage mainframe source code and deployment workflows via BMC Compuware ISPW, supporting assignment, task, release, and deployment operations.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.