> browse/registry

> openai-realtime

Build voice-enabled AI applications with the OpenAI Realtime API. Use when a user asks to implement real-time voice conversations, stream audio with WebSockets, build voice assistants, or integrate OpenAI audio capabilities.

> openai-sdk

Integrate OpenAI APIs into applications. Use when a user asks to add GPT or ChatGPT to an app, generate text with OpenAI, build a chatbot, use GPT-4 or o1 models, generate embeddings, use function calling, stream chat completions, build AI features, moderate content, generate images with DALL-E, transcribe audio with Whisper API, or integrate any OpenAI model. Covers Chat Completions, Assistants API, function calling, embeddings, streaming, vision, DALL-E, Whisper, and moderation.

> openapi-spec

Design and maintain OpenAPI specifications. Use when a user asks to create an API spec, document REST APIs, generate client SDKs from a spec, validate API contracts, or implement design-first API development.

> openclaw

Deploy and manage OpenClaw, a self-hosted gateway bridging messaging platforms to AI coding agents. Use when a user asks to set up OpenClaw, connect WhatsApp or Telegram or Discord to an AI agent, configure multi-agent routing, schedule cron jobs in OpenClaw, set up webhooks, manage OpenClaw channels, pair a messaging account, configure heartbeats, spawn sub-agents, or troubleshoot OpenClaw gateway issues. Covers installation, channel setup, agent configuration, cron scheduling, webhooks, and su

> opencv

You are an expert in OpenCV (Open Source Computer Vision Library), the most popular library for real-time computer vision. You help developers build image processing pipelines, object detection systems, video analysis tools, augmented reality, and document processing using OpenCV's 2,500+ algorithms for image manipulation, feature detection, camera calibration, 3D reconstruction, and DNN inference — in Python, C++, or JavaScript.

> streamlit

Expert guidance for Streamlit, the Python framework for building interactive data applications and dashboards. Helps developers create web apps for data exploration, ML model demos, and internal tools using pure Python — no frontend skills required.

> mise

Manage tool versions and tasks with mise (formerly rtx). Use when a user asks to manage Node.js/Python/Go versions per project, replace nvm/pyenv/asdf, or define project-level tool requirements.

> mixpanel

Product analytics with Mixpanel — event tracking, funnels, retention analysis, user segmentation, and A/B testing. Covers JavaScript SDK for frontend tracking, server-side tracking with Node.js and Python, identity management, group analytics, and the Query API. Use when tasks involve tracking user behavior in web or mobile apps, building conversion funnels, analyzing retention curves, or running experiments.

> mkdocs

Build documentation sites with MkDocs and Material for MkDocs. Use when a user asks to create project documentation, configure MkDocs themes, add search and navigation, deploy docs to GitHub Pages, or customize Markdown extensions.

> mlflow

Open-source platform for managing the ML lifecycle. Track experiments with metrics and parameters, register and version models, deploy models to various targets, and build reproducible ML pipelines. Integrates with all major ML frameworks.

> mobx

You are an expert in MobX, the simple and scalable state management library based on transparent reactive programming. You help developers build React applications with observable state, automatic tracking of dependencies, computed values, actions for state mutations, and reactions for side effects — providing a natural, class-based or functional approach where the UI automatically updates when state changes without manual subscriptions.

> mockoon

When the user wants to create mock API servers locally using Mockoon with its GUI or CLI. Also use when the user mentions "mockoon," "API mocking," "mock server," "mock API," "OpenAPI mock," or "local API simulation." For programmatic HTTP mocking, see wiremock.

> modal

Serverless GPU compute platform for running Python functions in the cloud. Deploy ML models, run training jobs, and serve inference endpoints without managing infrastructure. Supports A100/H100 GPUs, custom container images, and scales to zero automatically.

> mojo

Expert guidance for Mojo, the programming language by Modular that combines Python's usability with C-level performance. Helps developers write high-performance AI/ML code, optimize numerical computations with SIMD and parallelism, and gradually port Python code to Mojo for orders-of-magnitude speedups.

> stripe-billing

You are an expert in Stripe Billing, the complete billing platform for SaaS businesses. You help developers implement subscription management, usage-based billing, metered pricing, free trials, proration, invoicing, customer portal, and webhook-driven lifecycle management — building everything from simple monthly plans to complex per-seat + usage hybrid pricing.

> stripe-testing

Test and debug Stripe payment integrations. Use when someone needs to verify webhook handling, simulate payment flows, debug failed charges, validate subscription lifecycle, or troubleshoot Stripe API errors. Trigger words: stripe, payment testing, webhook debugging, charge failed, subscription error, payment intent, checkout session.

> structlog-python

Add structured logging to Python with structlog. Use when a user asks to implement structured logging, add context to Python logs, configure log processing pipelines, or replace standard logging with typed output.

> structured-output

Force LLMs to return typed, validated JSON — not free-text. Use when someone asks to "get structured data from LLM", "parse LLM response as JSON", "make AI return typed output", "validate LLM output", "extract structured data with AI", "use instructor with OpenAI", or "get reliable JSON from Claude/GPT". Covers OpenAI structured outputs, Anthropic tool_use for structured data, Instructor library, Zod schemas, Pydantic models, and retry strategies for malformed responses.

> mongodb

Assists with designing document schemas, building aggregation pipelines, managing indexes, and operating MongoDB clusters. Use when working with flexible schemas, nested documents, horizontal scaling, Atlas Search, or vector search for AI applications. Trigger words: mongodb, mongo, document database, aggregation, atlas, nosql.

> mongoose

You are an expert in Mongoose, the elegant MongoDB object modeling library for Node.js. You help developers define schemas with validation, build queries with a fluent API, use middleware hooks, populate references, create virtual fields, and handle transactions — providing structure and type safety on top of MongoDB's flexible document model.