Official Model Studio CLI（阿里云百炼 CLI）built for AI Agent frameworks, exposing models, search, multimodal, and workflow capabilities as structured tool calls.

Jev-compatible API server for open decision models. Ollama for decision models: pull and serve 29 model families (Laya, pplx-decider, Clef, Winnow, coba...) locally or self-hosted behind /v1/systemone. The TypeSafe SDK works unchanged: set its base URL and pick an open model. CLI, desktop app, Docker, MCP server, public bench.

Own your AI. The native macOS harness for AI agents -- any model, persistent memory, autonomous execution, cryptographic identity. Built in Swift. Fully offline. Open source.

You're the boss, agents are your team. They handle tasks on their own, message each other, and review each other's work. You just watch the kanban board and give high-level commands. Codex/Claude/OpenCode/Cursor/Grok/GitHub/Kiro/Z.AI/Xiaomi/MiniMax/Kimi(300+ models, 200+ LLM providers, free models no auth) Build your AI company with multiple teams

Enables MCP-compatible clients to send prompts or conversations to Chinese LLM models, list available models with pricing, and compare responses from multiple models through an OpenAI-compatible API.

Discover inspiration and create images and videos with the latest AI models. Works with ChatGPT, Claude, Cursor, and other MCP clients.

Guardian agent for AI coding: four frontier models review risky diffs and commits before they ship.

💻 Give AI models complete control of your computer (probably a bad idea)

Generate images, video, audio and short films with 140+ AI models from any MCP client.

Fastest enterprise AI gateway (50x faster than LiteLLM) with adaptive load balancer, cluster mode, guardrails, 1000+ models support & <100 µs overhead at 5k RPS.

Run local AI across all your computers. Toskar's MCP server lets Claude, Cursor, and other clients ask your own local models and search your connected knowledge, with nothing leaving your machines.

Lets Claude and other MCP clients hand coding tasks to the Codex CLI as a sub-agent, running under the user's own Codex configuration so any configured model provider (OpenAI, DeepSeek, local models) does the work. Provides tools to start, poll, cancel and inspect jobs with compact change summaries, long-task handling, token-saving lean mode and clean process teardown.

Enables Codex to delegate subtasks to concurrent background coding agents that can each run on any model provider supported by Pi, such as DeepSeek, Anthropic, Gemini, OpenRouter, or local models. Exposes MCP tools for listing models, spawning and waiting on agents, sending follow-ups, and aborting, backed by a live local web panel showing status, token usage, and streaming output.

Gemini provider for Pi on the Antigravity ACP server (official Google ACP) or the stream-json agy CLI. Use antigravity/* models in Pi. Full /model picker support. Models runs Pi's tools. ToS safe to use.

Enables MCP clients to drive the 4NEC2 NEC-2 engine for natural-language antenna modeling and simulation, including building Yagi models, calculating impedance/SWR/gain/front-to-back ratio, sweeping frequency, parsing .out files, optimizing geometry, and generating pattern/sweep plots.

Voxel editor with an MCP server: build and edit MagicaVoxel .vox models, add bones and animation clips, run Rhai generator scripts, path-trace PNG previews, and export glTF.

Enables MCP clients to discover NVIDIA, AMD, and Intel GPUs, monitor utilization, memory, temperature, power, clocks, and processes, retain bounded local history, and estimate whether AI models fit available VRAM before loading them.

Enables local synchronization of Garmin activity and health data using a personal API key, then lets MCP-connected AI clients analyze training readiness and recovery with cited models and research. Supports viewing records, sleep/HRV, stress, Body Battery, and generating pre-run recommendations without hosting accounts or personal data.

MCPSharp is a .NET library that helps you build Model Context Protocol (MCP) servers and clients - the standardized API protocol used by AI assistants and models.