"Exploring MCP for Backend Development" matching MCP servers:

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.

Provides access to PatternFly React documentation, development rules, and component schemas through MCP tools, enabling AI assistants to help developers build applications with PatternFly components following best practices.

Provides an institutional research backend for AI assistants, with 15 tools for company, financial, funding, competitor, industry, and news intelligence, plus Markdown/PDF report generation, featuring deterministic source routing, extraction, validation, and citation generation.

Enables AI assistants to automate mobile app testing and development for iOS and Android through natural language interactions. Supports intelligent element identification, session management, automated test generation, and comprehensive device interactions including clicks, swipes, screenshots, and app management.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

A local bridge that lets MCP clients inspect, export, and modify Figma files through a development Figma plugin.

Enables users to manage API keys and perform Aptos Build actions through MCP-compatible interfaces like Claude and Cursor. This server facilitates development workflows on the Aptos blockchain by integrating directly with the Aptos Build platform.

A flexible proxy server that aggregates multiple backend MCP servers into a single interface using STDIO or SSE transports. It supports dynamic server management via an HTTP API and utilizes namespacing to prevent tool conflicts across connected services.

Integrates front-end development servers with AI tools, enabling browser automation, console log capture, screenshot management, and HMR event monitoring.

Habitica MCP server built with Effect v4, currently exposing a hello-world tool, resource, and prompt over stdio for early development and testing.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.