"Retrieve Website Titles Based on Given URLs" 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.

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 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.

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.

Enables Codex to use an installed Devin CLI as an additional worker by starting, polling, and cancelling bounded tasks through local MCP tools. It runs as a local stdio server in a given working directory, so jobs execute with the Devin account's model and permissions while Codex's own routing rules still decide when to delegate.

Enables parallel execution of shell commands and AI coding agents (Claude, Gemini, Codex) across lists of items like files or URLs, with batched processing and real-time streaming output for batch operations.

Enables multiple AI agents to coordinate work on the same codebase by providing real-time file locking, commit approval, and agent awareness through a lightweight WebSocket-based MCP server.

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

Enables AI assistants and MCP clients to launch and manage Cursor Cloud Agents on repositories or without one, select models, follow up mid-run, retrieve or cancel results, and check usage and cost.

MCP server that exposes Google Jules AI agent as tools, allowing local AI agents to list authorized repositories and delegate coding tasks to Jules, receiving session URLs for tracking.

Connects AI coding agents to a shared knowledge base by allowing them to search, retrieve, and contribute coding traces. It acts as a protocol adapter for the CommonTrace API, facilitating collaborative knowledge sharing through natural language queries and tool-based interactions.

Slimdex is a local MCP server that helps coding agents retrieve code narrowly—outlines, line ranges, symbol bodies, references, and intent-based searches—instead of reading whole files into context, featuring a persistent index and tools for exploration, editing, and session memory.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

ast-mcp-server gives coding agents compact, type-aware access to TypeScript and JavaScript projects, providing structural code tools based on the real compiler project model through ts-morph for declarations, references, renames, and diagnostics, with safe prepare → review → apply mutation semantics and immutable hash-bound plans.

Enables Codex CLI to delegate tasks to file-based specialized agents with isolated execution, auditability, and CI-friendly validation.

Orchestrates multiple Claude Code agents across iTerm2 sessions with process-level isolation, enabling collaborative AI development workflows on multiple codebases with task-based inter-agent communication and persistent state management.

Automatically generates compelling application specifications and code based on the four dimensions (existence, historicity, relationality, irrationality), simplicity, and Figma-like UI, enabling users to create great apps without detailed instructions.

An MCP server for Trae AI that enables automated creation and management of OpenSpec-compliant projects through natural language descriptions. It features tools for generating specification files, optimizing existing code based on specs, and deploying project templates without command-line intervention.

Outcome-based persistent memory for AI coding tools.