"The Models Resource" matching MCP servers:

Lets MCP clients delegate tasks to the Google Antigravity CLI, including starting and continuing conversations and listing models, while returning structured results over stdio.

Delegates coding tasks to the locally installed Kimi Code CLI, reusing its auth, models, and configuration while adding tools for sessions, replies, model discovery, live turn steering, and history access.

Production-ready MCP server starter templates in TypeScript and Python. Includes tool, resource, and prompt patterns with Claude Desktop integration configs.

Delegate tasks from Claude Code to other models (Codex CLI, DeepSeek, OpenRouter, etc.) without leaving the app.

Enables MCP clients to invoke Cursor SDK's agent runtime, run coding agents, list models, and continue conversations.

Provides free, unlimited access to Claude AI models via Puter.js for AI coding agents and IDEs through the MCP protocol.

Enables an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.

Enables MCP clients to run Cursor CLI agent prompts with any model the installed CLI offers, continue existing sessions, and list available models and sessions. Adds guarded execution with concurrency limits, timeouts, cancellation, and operator-gated auto-approval so multiple models can be run in parallel.

Add OpenAI (Codex) models to Claude code

Enables AI assistants to consult other AI models via OpenRouter for help with coding tasks.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

A lightweight MCP server that bridges OpenAI Codex to Gemini models via the Antigravity CLI, enabling natural language prompts and model listing within Codex.

Extended MCP server for OpenAI with support for GPT-5 family, Codex models, and automatic API endpoint selection, enabling chat interactions via the openai_chat tool.

Production-grade, autonomous Model Context Protocol (MCP) server that elevates AI models from stateless code generators into persistent, self-verifying software engineers.

An MCP execution layer that lets capable AI models safely control a developer workstation for file edits, terminal and process execution, Git operations, language-server analysis, browser and Windows UI automation, media processing, job/resource control, and checkpointing. It also coordinates durable single- or multi-agent tasks across providers with leases, dependency graphs, evidence logs, repair loops, and separate verification gates.

Exposes the Quebragalho pre-paid model gateway to MCP clients, letting coding agents like Claude Code, Codex, Cursor and OpenCode spawn separate repo-aware sub-agents that run on 17 frontier models, with background job tracking, routing tiers and persistent per-project memory.

Enables coding agents to check human-stated assumptions against authoritative sources like AWS AppConfig, Sentry, and the repository, detecting when beliefs have drifted from reality. It provides tools to inspect belief history, list verifiable properties, review open drifts, and record verified understanding.

Launches the official Codex CLI as a persistent MCP server so DeepSeek Harness can invoke Codex models without storing or transmitting ChatGPT credentials to third parties.

Enables Claude to hand off implementation tasks to OpenAI Codex models running through the Codex CLI, with tools for listing models, delegating work synchronously or in the background, collecting results, and continuing past sessions, while Claude stays the orchestrator that reviews diffs and runs tests.

Delegates autonomous coding tasks to Z.ai's GLM models with a genuine agent loop, file operations, and verification via git and real process results.