"MCP servers for general chat and backend development" matching MCP servers:

Enables coding agents to load backend anti-slop rules and deterministically audit TypeScript/backend files for violations like SELECT *, SQL interpolation, N+1 calls, silent catches, stack leaks, type escapes, and TODOs, plus verify TypeScript compilation. Returns PASS/FAIL findings so agents can fix issues before shipping.

Enables AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.

Provides comprehensive development tools for FastMCP projects including documentation access, NPM package version management, and TypeScript type definitions retrieval. Enables developers to fetch FastMCP documentation, analyze NPM packages, and access MCP architecture information through natural language.

MCP server for Next2D application development that generates code following MVVM + Clean Architecture + Atomic Design patterns, validates architecture, and provides API references.

A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.

Enables code reviews and analysis by connecting Codex to ChatGPT in Chrome.

An MCP server that enables analyzing and querying GitHub repositories through the GitHub Chat API, allowing users to index repositories and ask questions about their code, architecture and tech stack.

Provides comprehensive code analysis (quality, complexity, linting, dependencies, security) and web scraping capabilities (static/dynamic content, API discovery) for development workflows.

Enables local-first codebase intelligence, allowing chat, search, and audit operations on any repository with file:line citations, and supports offline deterministic modes without an LLM.

Reusable MCP server for Python backend development with FastAPI, MongoDB, and Stackraise support.

Enables AI-assisted development of CodeQL queries for security analysis through the Model Context Protocol. Provides tools for compiling, testing, and executing CodeQL queries across multiple programming languages.

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

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 AI IDEs to chat with, search, explain, refactor, and audit a local codebase without uploading source code, returning answers backed by file-and-line source citations, confidence scores, and severity labels, plus audit and board-ready strategic reports. Runs locally and standalone as an MCP server compatible with Claude, Cursor, Windsurf, and DeepSeek Harness.

This MCP server bundles a filtered copy of the Mern-Chat-App repository and exposes tools to list, read, and search files, as well as retrieve architecture overviews and file summaries.

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 backend test quality analysis for GPA e-commerce, including coverage analysis, reverse engineering, architecture mapping, and test suite generation.

Enables reverse engineering and binary analysis using Ghidra, YARA, Radare2, and other tools, plus backend development assistance like project analysis, security scanning, and scaffolding.

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.