"An overview or resources on Kubernetes" matching MCP servers:

Enables developers and product owners to scan a codebase and extract a readable business overview—features, roles, access control, data model, and endpoints—along with findings on missing or inconsistent rules, and generate shareable HTML or Markdown reports and diagrams.

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.

Gitbub mcp

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

RCP-1 is an enterprise-ready MCP server that connects AI assistants to SAP ABAP systems via the ADT REST API, with built-in security, access controls, and deployment options for BTP or on-premise.

MCP server for AI-assisted development on the Lampa open-source TV app, providing read-only access to the source tree with 41 tools and 5 resources for structured analysis, planning, editing, and validation.

Allows Claude Code to request an independent code review from Google Antigravity (Gemini, Claude, or GPT-OSS) via the Antigravity CLI, providing a second opinion on plans or diffs.

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.

Enables an AI assistant to debug ABAP code on a connected SAP system by setting breakpoints, running code, and capturing call stacks and variables, with one-shot or interactive stepping.

Exposes a project's Reado code-review annotations (tasks, comments, reading progress, bookmarks) as MCP resources, plus tools for an AI coding agent to resolve review tasks, drive guided pair reviews, and inspect Reado's live browser preview.

Enables coding agents to lint Dockerfiles and Kubernetes manifests through the Shipshape API, returning an A–F grade, score, pass/fail status, and every finding with its line, fix, and reference. Uses the user's own marketplace key, reports remaining plan quota, and explains errors in plain language.

Cartograph is an MCP server that provides agent-native code intelligence by building a queryable code graph from a repository using tree-sitter and SQLite. It offers tools for symbol lookup, call graph traversal, blast radius analysis, and architecture overview to help coding agents answer structural questions about code.

Enables consulting oracle AI models (Codex or Claude) for expert reasoning and analysis on complex problems, architectural decisions, and design tradeoffs through a unified CLI interface.

Enables AI assistants to statically lint and explain Kubernetes manifests, surfacing security, cross-resource, RBAC, and removed-API issues with line numbers and safe fixes without a cluster or kubectl. It also redacts secret values and supports Helm values review plus optional rendered-chart linting.

Click an element in your running web app or the iOS Simulator and say what should change; your coding agent gets the comment with the selector, DOM path, computed styles, component chain, source-file hint and a cropped screenshot. Runs locally on 127.0.0.1.

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.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

An MCP server providing 63 semantic analysis tools for Java, built directly on Eclipse JDT for compiler-accurate code understanding.

An MCP server that exposes e18e module replacement data. It helps AI assistants suggest lighter, faster, or native alternatives to common JavaScript/Node.js packages.

Enforces AST-based architectural guardrails on AI-generated code, blocking writes that violate maintainability, security, or complexity rules and prompting immediate refactoring.

Enables AI assistants to retrieve a project's architecture overview and file structure, auto-detecting monolith or multiproject layouts and exposing module listings to reduce token consumption.

An MCP server that performs comprehensive health checks on project dependencies for JavaScript and Python projects, detecting outdated packages and fetching changelogs.

Enables token-efficient semantic search and analysis over any directory of files through hybrid search, directory overview, structural analysis, and dependency graphs.

Enables running Prospector static analysis on Python files or directories via MCP, returning structured results with severity, location, and rule codes.

An MCP server that exposes Ruby on Rails implicit dependencies like callbacks, associations, and concerns to AI coding tools.

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

Enables agents to audit Kubernetes manifests without a cluster: scanning YAML text or whole directories with file:line evidence, browsing the rule catalogue with why/fix rationale, resolving RoleBindings into each subject's effective permissions, and running a self-check that the rules fire.

An unofficial MCP server that lets Codex ask a read-only OpenCode advisor for a second review pass on Git changes.

Provides a high quality cybersecurity tool platform with pay as you go pricing (no subscription).