"Lanyard ID Card Ribbon Mockup Set on Envato Elements" 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 reasoning agents to turn PRDs into production-ready applications by discovering and reusing existing features, UI components, database models, and templates, then planning, scaffolding, validating, and preparing Git changes for review.

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 coding agents to connect to Debug Adapter Protocol debuggers over MCP, allowing them to launch or attach to native targets, control execution, set breakpoints and watchpoints, inspect stacks, variables, memory, and exceptions, and capture agent-friendly debugger snapshots.

Enables MCP clients to run non-interactive Codex CLI sessions via codex and codex-reply tools, including resuming conversations by thread ID and passing codex exec flags.

Runtime governance and budget guardrails for Claude Code, Cursor, and autonomous AI agents. Enforces per-session spend caps, verifier safety gates, and runaway loop prevention.

Enables delegating coding tasks to the local cursor-agent CLI synchronously, blocking until completion and returning a compact report with diff, status, and session ID.

Enables MCP clients such as Claude Code, Codex CLI, and Cursor-agent to delegate bounded coding tasks to a local OpenCode v2.x installation via a single opencode_execute tool, returning the model's response, git diff/status summary, exit code, and session ID.

Enables AI coding agents to set budgets per task, check costs before expensive operations, and halt when budget is exhausted, with support for calibration and cloud sync.

Enables multiple AI coding agents to collaborate on a project by coordinating tasks, file leases, and messages through a shared hub, preventing conflicts and enabling parallel development.

A local stdio MCP server that lets any MCP client start a Codex thread and continue it by opaque thread ID through the codex and codex-reply tools, with fail-closed sandboxing and approval policies. It restores the removed Codex CLI MCP integration by bridging clients like OpenCode to the official Codex SDK.

Enables Codex to hand off coding tasks to a locally running DeepSeek Harness Desktop Host over MCP, reusing the Host's configured model and runtime and returning a session ID for status checks, incremental event streaming, waiting, and cancellation.

A Windows proof-of-concept MCP server that connects ChatGPT developer-mode to a local Codex CLI via Secure MCP Tunnel, exposing a small set of read-only, allowlisted tools in an isolated workspace.

Exposes a remote coding agent as MCP tools so an MCP client can delegate tasks, manage their lifecycle, and inspect the agent card, with permission decisions enforced inside the bridge.

Lets Claude Code, Codex, or any MCP client drive DeepSeek Harness as a long-lived coding agent: starting and resuming conversations, dispatching tasks in the background, streaming live output and reasoning stats, interjecting or interrupting mid-turn, handling approval prompts, and collecting results later. Sessions persist by ID, so work survives process restarts and can be handed back to a DSH GUI when needed.

Enables coding agents to inspect live browser runtime evidence, such as blocking elements and interaction surfaces, and to independently verify whether a code fix resolved the issue.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

Enables coding agents to read snapshots of inspected UI elements and attached notes, allowing visual feedback and context to be shared through MCP.

Visual feedback for AI coding agents on Astro sites, providing live annotations with source file:line, CSS selector, Tailwind classes, and computed styles.