"Managing Kubernetes Clusters on AWS Elastic Beanstalk" 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.

Provides AI coding agents with structured access to indexed codebases via semantic search, symbol analysis, and file reading tools.

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

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

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.

Enables AI agents to audit Kubernetes manifests for configuration traps that pass linters but silently break production, via read-only tools to audit YAML, list known traps, and explain trap details.

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.

Enables read-only querying of a local repository through a deterministic tree-sitter symbol and edge graph, exposing keyword search with exact file:line hits, regex text search, per-file symbol skeletons, caller/callee traversal, and directory-level maps of clusters, hubs, and hotspots over stdio.

Behavioral verification intelligence for AI coding agents. Reads a TypeScript or JavaScript repo, clusters functions into 25 semantic workflows (Authentication, Payments, Webhooks, Caching, Queue, and more), and emits concrete adversarial probes per workflow. 17 MCP tools, local SQLite state, zero cloud.

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.

An OpenAI-powered developer intelligence MCP server that scans GitHub repositories, extracts and clusters agent engineering patterns, analyzes local codebases, and proposes safe AGENTS.md improvements.

Enables coding agents to run deterministic, zero-dependency AST static analysis over source code, building call graphs and dependency metrics to find orphaned functions, unreachable methods, breaking API surface diffs, and token-bloat clusters, then return a structured refactoring plan. It plugs into MCP clients like Claude Desktop, Cursor, and Windsurf via a single Python entrypoint.

Enables deterministic AST static analysis and call-graph auditing to identify orphaned functions, unreachable methods, and token-bloat clusters, producing refactoring plans that reduce context waste.

nativegate is a code generator that produces MCP servers from legacy native codebases: point it at a Fortran deck or C++ header and it generates pybind11/f2py bindings, a Python package, a FastAPI service that exposes the native routines as MCP tools and REST endpoints, tests, Docker/Kubernetes manifests, and a numerical golden-record regression harness. The legacy numerics are never rewritten

Builds a dependency and topology graph of a Kubernetes/FluxCD GitOps repository via static analysis, enabling AI agents to reason about service relationships without cluster access.

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.

Exposes CodeRabbit IDE review comments as MCP tools and resources, allowing scanning, listing, and managing comments from clients like Cursor.

An MCP server that enables AI agents to perform automated code reviews on GitLab merge requests, including fetching details, reading diffs, posting inline comments, managing labels, and approving or unapproving MRs.

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.

Static audit of Kubernetes manifests via MCP, powered by kube-linter. Returns structured reports with severity, check ID, category, message, and remediation hints.

An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.

Compiler introspection for the Hirð language (typed actors and effect rows on the BEAM): type inference, definition lookup, effect-row explanation, IR fragments, actor protocol and supervision graphs, and token-budget-aware symbol summaries.

Zero-dependency context baton and compression server for AI coding agents. Hands off structured session state (.vicem/BATON.md) across Claude Code, Codex, Cursor, Gemini CLI, and 15+ agents, skeletonizes source code by 80-90% with lossless on-demand MCP rehydration (vicem_rehydrate), slims test logs by 95%, and redacts secrets locally.

Review and rewrite LangChain, LlamaIndex, Ollama, and XRPL code against current APIs, plus runnable examples, import lookup, and XRPL tx skeletons that never submit. Live docs included. $0.001 USDC on Base or 1000 drops XRP.

Official Codna MCP server with Mojo-powered risk simulation. Maps repos with zero LLM tokens. 5 stdio tools: triage, root-cause analysis and fix plans (optional PRs), SARIF reachability proof, on-device code memory and bug reporting. Introspection needs no credentials; execution requires a one-time free codna login. Source: cli/codna/mcp_server.py. Registry: io.github.thyn-ai/codna.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

Enables AI coding assistants to debug and analyze JavaScript in web pages by managing scripts, breakpoints, network and WebSocket traffic, browser state, and local file inputs/outputs for continuous reverse-engineering workflows.