"Top 100 MCP Servers Ranked by Weekly Downloads" matching MCP servers:

An interactive coding agent and MCP server that provides access to various AI models via the Tsinghua University lab proxy API. It enables users to inspect files and execute shell commands within their local directory using models like DeepSeek, GLM, and Qwen.

Enables LLMs to apply Martin Fowler's 71+ refactoring patterns to codebases through a pluggable, language-agnostic architecture. Supports previewing and applying refactorings, analyzing code smells, and inspecting code structure with safe-by-default operations.

A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools. Developed by Mammoth Growth.

Turn rough requests into rigorously structured prompts for any coding agent. Quality-scored to ≥90/100 across 12 dimensions, calibrated on 1,000+ real coding cases.

Provides accurate, source-grounded breaking-change briefings for npm packages by reading real GitHub release notes and CHANGELOGs, helping coding agents avoid hallucinated dependency migrations.

Wraps the Claude Agent SDK as MCP servers, letting you spawn multiple specialized Claude Code agents — each with its own model, tools, system prompt, and personality — from any MCP client.

Prevents coding agents from repeatedly attempting the same failed fix by tracking attempts and blocking further fixes until the agent uses its own web search tool.

Provides per-Subagent MCP controls to any coding agent or client across all your MCPs and prevents context window waste. Loads only 3 tools instead of all your MCP Server's tool definitions. Agents discover tools on-demand, only when needed and only the servers and tools they are allowed.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

An MCP server that enables autonomous code development by pulling GitHub issues, fixing them in a sandboxed environment, running tests, opening PRs, and promoting to production upon human approval.

Official implementation of Anthropic's 'think' tool that provides Claude with a dedicated space for structured reasoning, improving performance by up to 54% on complex tasks requiring multi-step problem solving.

A fully featured coding agent that uses symbolic operations (enabled by language servers) and works well even in large code bases. Essentially a free to use alternative to Cursor and Windsurf Agents, Cline, Roo Code and others.

Enables multi-model code review by fanning out issues to multiple LLMs simultaneously, diffing their unique insights, optionally running debate rounds, and dispatching subagents to implement fixes with git commits.

A personal AI coding assistant that connects to various development environments and helps automate tasks, provide codebase insights, and improve coding decisions by leveraging the Model Context Protocol.

Enables coding agents to design first by interviewing users, refining specs in digestible chunks, producing bite-sized TDD plans, and autonomously executing them through subagents with a server-verified red/green testing gate.

A TypeScript MCP server for launching, tracking, and managing external coding-agent runs across local and remote backends like Codex and Claude Code. It allows top-level agents to orchestrate subagents through tools for spawning tasks, polling events, and handling interactive sessions.

Enables AI assistants to incrementally build Laravel and Vue.js applications by creating file structures, methods, and code through natural conversation.

Executes development tasks by bridging Claude Desktop with Claude Code CLI, enabling automated code generation and task completion in specified working directories.

Enables non-coders to build software by describing ideas in natural language, orchestrating AI agents and CLI workers via chat without needing a terminal.

An MCP server that automates code review by providing syntax checking, code explanation, and improvement suggestions using a multi-agent system.