"AI-assisted Code Refactoring Tools and Techniques" matching MCP servers:

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.

Analyzes Python code and provides guided refactoring suggestions without automatically modifying code.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.

Provides TypeScript and JavaScript code refactoring operations using ts-morph, allowing AST-based symbol renaming, file/folder renaming, reference searching, and path alias removal when integrated with editor extensions like Cursor.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

MCP server for personal knowledge management providing AI-powered tools for semantic search, audio transcription, image generation, and PPT creation.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

An MCP server that lets Claude Code delegate coding tasks such as code generation, review, refactoring, and test writing to a local Ollama instance running a Qwen3 model.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Renders source code as beautiful SVG or PNG images with syntax highlighting, line numbers, and diff support. Ideal for AI agents to present code visually to humans or for sharing snippets.

Provides five safe tools (calc, search, model_drift, compare_runs, grade_answer) for arithmetic, keyword search, model drift monitoring, eval comparison, and answer grading against sources, all implemented directly from the MCP spec with zero dependencies.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

A code review tool server based on Model Context Protocol (MCP) providing multi-dimensional code review and scoring.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

Enables AI assistants to search YouTube, fetch transcripts, and get AI summaries of videos without API keys.

Provides comprehensive code quality analysis with quantitative metrics, historical trends, and refactoring risk prediction for C#, Python, and TypeScript codebases.

Enables querying MITRE ATT&CK and D3FEND data efficiently, providing techniques, detections, mitigations, actors, and countermeasures with token-aware summaries and paginated graph traversal.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.