"A Linux system administration tool for viewing system details and files" matching MCP servers:

Provides structured instructions to Cursor for generating comprehensive system summaries of Node.js/TypeScript codebases.

Read-only MCP tools for coding agents to audit deployment targets, detect fabricated code, review backlog, database schema, analytics, ML models, architecture docs, and decision lenses.

Enables AI agents to create, validate, and export UML system models using structured MSON format. Supports generating PlantUML and Mermaid diagrams with direct export to System Designer macOS application.

Fetches, summarizes, and reviews GitHub code diffs with asynchronous processing for large diffs.

Provides a real API for coding agents to look up design system components, props, and tokens, preventing guessed answers.

Enables coding agents to read ground truth about a React design system — components, props, cva variants, tokens and docs — over MCP so they write UI that matches it. It also exposes a check_ui linter agents run on their own output, returning rule ids, locations and concrete fixes before review.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

A Python-based system that provides AI-powered code reviews through simulated expert personas like Martin Fowler and Robert C. Martin, using the Model Context Protocol (MCP).

Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.

Governed development control plane for VedaOps projects, letting authorized agents inspect, search, patch, test, lint, and coordinate registered software without exposing a general shell.

An enterprise-grade AI processing platform that provides advanced code analysis, automated documentation generation, security scanning, and knowledge extraction capabilities through a scalable MCP architecture. Features iterative neural processing, support for 100+ programming languages, and real-time streaming updates.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

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.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Enables Claude Web to securely inspect, search, and modify local project files through a sandboxed MCP server with atomic writes, path traversal protection, and sensitive file blocking.

Provides real-time TBC Bank development standards compliance checking and code review tools. Integrates with GitHub Copilot and development workflows to automatically enforce coding guidelines and reduce violations.

An MCP server that analyzes Python codebases using AST, stores code elements in a vector database, and enables natural language queries about code structure and functionality using RAG with Google's Gemini models.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

Enables MCP-compatible AI clients to inspect Godot project and editor state, observe opted-in running scenes, manage processes, and apply permission-scoped guarded edits. It starts read-only and exposes additional capabilities only through explicit command-line flags.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

Enables AI assistants to import binaries into Ghidra, trigger analysis, browse functions, symbols, strings, and imports, and read decompiled C code and disassembly via MCP tools.

Enables binary comparison capabilities by leveraging IDA Pro and BinDiff to analyze similarities and differences between files. Users can perform automated function analysis to identify changed functions and compare original binaries against patched versions.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.