"A guide to analyzing and fixing SEO on a webpage" matching MCP servers:

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

A lightweight MCP bridge that lets Claude Code delegate heavy tasks to the Antigravity CLI - saving context window and tokens for what matters.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

Connects ChatGPT to Roblox Studio's built-in MCP, enabling natural-language reading and writing of game data, including executing Luau code and modifying scripts and instances.

MCP server that parses .sketch design files into CSS-aligned, LLM-friendly JSON, enabling AI coding agents to generate high-fidelity HTML, Vue, or React code.

An authenticated OpenAI-compatible inference gateway with an async job broker that bridges a coding agent to a ChatGPT MCP worker, enabling ChatGPT to process inference requests via a tunnel.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Enables AI assistants to write and execute C# code directly inside Autodesk Civil 3D, providing full API access through code generation and execution.

Enables Codex to delegate coding tasks to an OpenCode CLI locally, returning structured results such as exit codes, session summaries, tool calls, and git diffs.

Enables Codex to delegate coding tasks to Grok Build CLI, with Codex handling planning and review while Grok executes.

Enables two-model orchestration where Gemini in Google Antigravity delegates coding tasks to Qwen 3.8 Max in Qwen Studio Desktop via CDP, managing prompt delivery, file generation, continuation, and verification.

Bridges Claude Desktop with Claude Code CLI to delegate complex coding tasks like creating React apps, building APIs, and debugging scripts while maintaining interaction through the Desktop interface.

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.

Enables AI coding agents to retrieve relevant execution context before a task, compare candidate paths, log outcomes, and search past experiences stored locally in SQLite. It lets agents reuse what worked on similar tasks and get live alerts when a run stagnates or repeats failures.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

Enables Claude Code to use GLM (Zhipu) as a cheap, full-capability subagent for file editing, code generation, and bash commands, with automatic routing between Opus and GLM based on task complexity.

A generic OpenAI-compatible subagent MCP server that lets Claude Code delegate coding grunt-work to a local model via a tool-calling agent loop, with configurable concurrency and backend.

Get a second opinion on your code from every coding agent you have. Claude Code, Codex and Grok review each other's diffs and answer each other's questions, even inside a session that's already running. Uses the CLIs you're signed in to, no API keys.

Enables multiple AI agents to collaborate on the same git repository by coordinating work via a shared claims branch, detecting file conflicts before they happen.

Delegate a Cursor task to a real, unattended background OpenCode agent — cheaper model, isolated history — through five small MCP tools.

MCP server for agent-native evolutionary optimization. Enables agents to join runs, submit gate-checked mutations, and collaborate on evolving code toward a stated goal.

A robust, language-agnostic Model Context Protocol (MCP) server that provides AI coding agents with the ability to edit files surgically via Abstract Syntax Trees (AST) instead of relying on token-heavy, brittle search-and-replace or diff operations.

Enables handing one self-contained job to the Claude Code CLI on the local machine and getting back its final message plus a manifest of the artifacts it produced, without letting Claude write into the user's project. Reads are limited to named directories and all writes stay in a throwaway run directory, so the user reviews the listed files and copies in only what they approve.

Allows two AI coding agents on different machines to securely pair and share files, context, and conventions through an end-to-end encrypted peer-to-peer channel with human-in-the-loop consent.

An MCP server that lets coding agents scaffold, run, and iterate on Maltego transforms against a live local server, reading back entity results to validate and improve mappings.