"Using the web version of Perplexity AI" matching MCP servers:

Enables intelligent code analysis and debugging through the Perplexity AI's API, offering detailed error analysis, pattern detection, and comprehensive solutions, with integration support for the Claude desktop client.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.

Enterprise-grade code intelligence server for AI assistants that analyzes codebases for due diligence, tech debt, security vulnerabilities, and code quality.

Exposes 11 agent-native QA tools over stdio so coding agents can discover a project, analyze risk, select the smallest relevant test set, generate and dry-run tests, triage failures, propose tiered heals, analyze flakes, generate quality reports, and evaluate release readiness. Planning and healing tools stay read-only or propose-only, while execution defaults to dry-run, keeping agent actions safe and evidence-backed.

Enables AI agents and MCP clients to compute real-time, in-memory unified diffs between versions of live artifacts along with structured change telemetry. It runs as a deterministic, zero-dependency Python MCP server that plugs into Claude Desktop, Cursor, or Windsurf for diff and change-tracking workflows.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

AI development assistant with 36 specialized tools for memory management, code analysis, project planning, and problem-solving through natural language interactions in Korean and English.

An MCP server that generates, runs, and triages tests by introspecting Python modules or web pages, using structured LLM outputs for scenario generation and failure analysis.

A tool for vibecoding personnel and non-programmers to perform static code audit, query knowledge graph, and generate project documentation via MCP protocol.

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.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

An MCP server that reduces AI coding agent token usage by 80-99% through a queryable knowledge graph of code, change tracking, and persistent memory across sessions.

Provides AI coding agents with ground truth about a Rails app via 45 read-only tools covering schema, models, routes, controllers, views, jobs, and conventions, working over MCP or CLI and functioning even when the app cannot boot.

MCP server for Angular 19+ development, providing PR review, code scaffolding, modernization audits, and Storybook guidance.

Enables IDE integration with a multi-agent AI pipeline for solving, reviewing, and optimizing code through adversarial peer review and security filtering.

An MCP server that automates pull request reviews using multiple LLM providers (OpenAI, Claude, Gemini, Groq, Perplexity) and supports GitHub and Bitbucket with real-time webhook integration and interactive AI assistant commands.

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

Regex AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

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