"Setting up an MCP server in Kubernetes" matching MCP servers:

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

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

MCP server for ai-scanner that enables AI agents to scan codebases for LLM usage, AI frameworks, and exposed secrets.

In-memory polyglot AST pruning and deterministic context firewall for coding agents, eliminating up to 72.4% token bloat with zero telemetry egress.

Translates a lockfile diff into a human-readable upgrade plan. For every dependency bump (npm or PyPI) returns semver class, breaking changes from GitHub release notes, CVEs fixed in the range, migration guide links, and a clear per-package recommendation. Bulk tool ranks up to 50 package changes in parallel by risk (security > caution > review > likely-safe > safe).

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.

Parses Unity text-serialized .prefab, .unity, and .asset files to output only Inspector-visible data in hierarchical YAML, reducing token usage by up to 96%.

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.

MCP server that reduces token consumption in AI coding assistants by up to 90% via structural reads, PreToolUse hooks, and tp-\* subagents.

Enables Claude to look up known vulnerabilities in a project's dependencies across OSV.dev, CVE.org, NVD, CISA KEV and EPSS, then rank the findings by real-world exploitation so the most urgent fixes surface first. It supports single-package checks, keyword CVE searches, and whole-lockfile scans, with upgrade-path reasoning.

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.

An MCP server for querying the TheAlgorithms organization across all language repos, enabling search and retrieval of algorithm implementations with in-file examples.

Enables agents to validate JSON, JSONC, YAML, and TOML configuration files against official SchemaStore schemas, pinpointing errors and likely key misspellings, and to look up schema-backed setting details.

Enables an MCP-capable assistant to review GitLab merge requests, GitHub pull requests, and pre-push local branches against ticket requirements, domain rubrics, compiler/lint pre-passes, blast-radius analysis, and SonarQube findings, and to draft inline comments or follow-up tasks in the user's chosen language. Nothing reaches a remote host until a human approves the exact content in an interactive terminal.

An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.

Enables smart code search in your editor using natural language queries, building an index of your workspace.

An intelligent MCP server that analyzes logging quality in your code and provides improvement suggestions using LLM-powered insights.

An MCP server providing 15 semantic analysis tools for GDScript, powered by Godot's built-in Language Server.

An MCP server that gives AI assistants tools to generate AccelByte AGS uGUI prefabs in Unity projects, look up AccelByte Unity SDK best practices, search Bytewars C# example components, and configure SDK credentials from a Claude Code or Cursor session.

Exposes search, locate, expand, and find_related tools over MCP so AI coding agents in Claude Code, Cursor, Copilot, and other clients can retrieve the best code chunks (path, lines, snippet) by meaning instead of grep or glob. This hybrid code search lets agents find the right files in fewer steps, using up to 50% fewer tokens.

An MCP bridge that enables Claude Code to consult the Kimi AI model in a structured challenge-loop for code review, debugging, and architecture evaluation.

An AI Security Guardian MCP server that provides real-time vulnerability scanning, secrets detection, and secure coding enforcement for AI-generated code in modern web frameworks.

Enables multi-model AI code review from inside supported coding tools, reporting where up to four models agree and disagree.

Indexes your codebase so AI coding agents can search instead of re-reading files, saving up to 94% of tokens.

An MCP server for verifying AI-generated code quality, security, and performance, addressing trust gaps in AI coding assistants.

Enables AI agents to analyze large codebases and document collections by consulting large context window models (up to 2M tokens) via OpenRouter when files exceed the current agent's context limits.

An MCP server that provides ultra-efficient code exploration through AST analysis, reducing LLM token usage by up to 95% while enabling instant call graph generation and dependency analysis for massive codebases.

Enables explanation of peer-dependency conflicts in an installed package tree as a graph, including unsatisfied edges and least-change resolutions that satisfy every listed peer range.

An MCP server that folds function and class implementations into structural skeletons while preserving signatures, interfaces, and docstrings, reducing tokens by up to 90%+ for AI agents. Exposes tools to get repository skeletons, unfold specific symbols on demand, and retrieve exact token and prompt cost savings metrics.