"A server for data engineering tasks, GPU clustering, nomad setup, and data pipeline management" matching MCP servers:

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

MCP server that enables AI coding assistants to audit repositories against engineering rules, generating self-contained HTML reports with citations and optional GitHub issue filing.

Enables teams to structure metric definitions, compare semantic differences, detect JOIN fanout and drift, reconcile mismatched numbers layer by layer, and persist metric contracts as YAML.

Enables auditing a repository's Claude Code setup, scoring it from 0 to 100, and scaffolding agents and hooks to fix issues.

Enables verification of AI coding agent self-reports against git diff truth and a deterministic gate, producing pass/regenerate/reject directives to ensure claimed work matches actual changes.

Exposes 18 typed tools that drive real static-analysis engines (Ghidra, apktool, WABT, TShark, evmole, Rizin) over a single MCP endpoint to decompile binaries, audit APKs, scan EVM contracts, inspect WebAssembly, firmware, SQLite, and pcap data. Every call returns signed, verifiable evidence with an evidence_id, provider identity, SHA-256 artifact digest, and explicit limitations for security research, malware analysis, forensics, and CTF work.

Enables AI clients to inspect backend systems through structured engineering tools including Git history, Winston logs, OpenAPI contracts, and sandboxed source code.

Enables AI coding environments to enforce engineering governance through MCP tools and resources for init, check, route, and review workflows.

Analyzes code repositories and generates comprehensive documentation published to Google Docs with Mermaid diagrams.

Enables MCP-compatible agents to perform read-only inspection of OpenPLC Editor projects, including retrieving project structure and listing programs, function blocks, and functions.

A Chinese-friendly, locally running MCP server for WeChat Mini Program engineering, helping developers break down ideas into actionable tasks, inspect projects, generate blueprints, and perform security scans.

An MCP server plugin for Claude Code that analyzes local AI session logs to provide coaching on coding patterns, tool usage, and productivity insights via tools and slash commands.

Provides persistent memory and semantic code understanding for AI assistants using MongoDB Atlas Vector Search. Enables intelligent code search, memory management, and pattern detection across codebases with complete semantic context preservation.

Enables decompilation and reverse engineering of Java JAR files through multi-engine decompilation, candidate evaluation, Maven project structuring, AST-based deobfuscation, and bytecode comparison.

A sandboxed MCP tool for reverse engineering that provides a unified interface to various reverse engineering tools with security restrictions.

Enables AI coding agents to ground dependency setup, compatibility checks, and major-version migration advice in a project's real runtime, lockfiles, and config files. It parses local project state and npm registry metadata deterministically, then returns tag-pinned install commands, breaking changes, and upgrade steps rather than generic documentation.

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.

A Python MCP server that decompiles Android APK/XAPK/JAR/AAR files and extracts HTTP APIs used by the app.

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 read-only, workspace-bound inspection of repositories and log files, returning JSON reports with file counts, largest files, TODO/FIXME markers, and warning/error counts.

A Rust MCP server that indexes codebases into a property graph and provides tools for code intelligence, such as searching, context, impact analysis, and change detection.

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.

Enables AI agents to deterministically inspect, author, convert, validate, and diagnose Classical CAN and CAN FD databases and trace logs, including bit-layout validation, template generation, trace aggregation, ISO-TP/UDS reassembly, bus-health analysis, and reverse engineering.

A Ghidra MCP server that enables AI language models to interact with Ghidra for reverse engineering tasks, providing small, context-efficient tools to reduce hallucination and handle large binaries.

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

This server provides a two-tier autonomous framework for reverse engineering binaries and applications, balancing fast, low-token triage with deep, high-fidelity emulation. It enables agents to perform advanced tasks like decompilation, control flow analysis, and formal security auditing.

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.