"AWS" matching MCP servers:

Provides guidance and tools for the AWS Cloud Development Kit, including infrastructure patterns, GenAI constructs, and security compliance via CDK Nag. It streamlines development by generating Bedrock Agent schemas and providing comprehensive documentation for Lambda layers and AWS Solutions Constructs.

Scans code strings for hardcoded secrets (AWS keys, tokens, private keys, etc.) and returns redacted findings, helping AI coding agents catch secrets before writing or committing code.

Scans diffs, files, and snippets for leaked secrets like AWS keys, GitHub tokens, and private keys, returning redacted findings while running fully locally without network calls.

MCP server for detecting publisher telemetry pipeline leaks in binary artifacts by scanning for sensitive strings like Sentry DSNs, Slack tokens, and AWS keys.

Enables AI coding agents to search a security corpus, scan Terraform plan JSON for cited findings, and list sources via MCP tools grounded in CIS AWS Foundations and OWASP Top 10 CI/CD risks.

Enterprise-grade MCP server for SAP ABAP development, enabling AI-powered coding assistance through Amazon Q Developer and Kiro with 15 SAP development tools.

An MCP server that extends kali-mcp with cloud (AWS/Azure/GCP), API/GraphQL/JWT, OSINT, container/K8s, IaC/SAST, mobile, binary analysis, and reporting tools, all accessible via an HTTP MCP endpoint.

A personal workspace management server that provides automated project documentation reference, AWS/Fly.io infrastructure access, markdown-to-PDF conversion, and code analysis capabilities for Cursor IDE.

A local-first MCP server that gives AI coding agents runtime visibility and AI-managed debug logging. It replaces blind print() debugging by turning runtime execution into causal chains, allowing agents to instantly locate bugs by finding missing .success events in Python and TypeScript code. Single binary with MCP, CLI, and HTTP interfaces.

A self-hosted MCP server that fetches live documentation and performs code audits using real-time authoritative references to prevent AI hallucinations. It provides tools for searching documentation across 330+ libraries and scanning local source code for security, performance, and accessibility issues.

Integrates Checkov, Semgrep, Bandit, and ASH to provide comprehensive code security analysis for AI coding assistants.

Deterministic AST deconstruction and runtime circuit breaker preventing rogue shell escapes, dynamic eval(), and covert lateral socket egress in autonomous LLM tool calls.

MCP Blast-Radius Auditor — statically extract what an MCP server can touch and detect declaration divergences against manifest.json. Stdio MCP (mcp-blast-radius) plus CI gate (mcp-blast-radius-gate). pip install mcp-blast-radius==0.2.0

An MCP server for auditing and analyzing user interfaces across 20 platforms based on 30 fundamental UX laws. It provides automated code detection, platform-specific checklists, and comparative analysis to optimize design usability.

Enables an AI assistant to inspect GDSII layouts and stackup files, validate model scripts without running them, and generate AWS Palace models locally, along with layout previews, gmsh visualisation, S-parameter summaries, and inductor/capacitor value extraction. It works on files in the user's own Python environment and disk, without invoking the Palace solver.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables AI assistants to leverage VS Code's language intelligence for code navigation, refactoring, and analysis via the MCP protocol.

Enables AI coding assistants to run static analysis on GitHub repositories, raw code snippets, or local directories to detect cloud cost leaks in Terraform/AWS configs, PostgreSQL migration table-lock hazards, and OWASP/Next.js API security gaps. Each finding returns structured severity, line-level detail, and drop-in fixes.