deploy
AI Operations Team — Deploy: Model serving, inference APIs, blue/green deploys, rollback, and canary releases for production ML.
Paquete de plugins · de tonone-ai
Resumen
deploy es un paquete de plugins para herramientas de programación con IA publicado por tonone-ai. Marketplaces que leemos y que lo publican: 1 (Community GitHub marketplaces). Lo vimos por primera vez el 2026-11-09 y desde entonces no hemos registrado cambios. Según nuestra pasada por los marketplaces del 2026-11-09.
Qué pide
- Se instala como paquete de plugins
Ninguno de los marketplaces que leemos publica sus herramientas ni los ajustes que pide.
Lo que declara, pide y ejecuta, completo
Instala solo plugins de desarrolladores en los que confíes. Mostramos lo que publican los marketplaces y no probamos plugins.
Funciona con
- Claude Code
Según los marketplaces que lo listan y el transporte MCP que declara, tal como lo documenta cada cliente. No probamos plugins.
Conectar
Comandos y configuraciones generados solo a partir de lo que declaran sus marketplaces. No los ejecutamos por ti ni probamos plugins.
Como plugin de Claude Code
Generado a partir de lo que declara Community GitHub marketplaces.
/plugin marketplace add tonone-ai/tonone
/plugin install deploy@tonone-aiDónde está publicado
| Marketplace | Estado | Versión | Cifras | Verificado | Visto por primera vez |
|---|---|---|---|---|---|
| Marketplace de la comunidad tonone-ai/tonone (Abrir el código en GitHub) | Publicado | 1.19.0 | Sin cifra publicada | Sin marca |
Cada cifra es del propio marketplace y nunca se suma entre marketplaces. Un marketplace que no publica cifras no muestra ninguna: sin número no es cero.
Figura en un marketplace de la comunidad
| Marketplace | Repositorio | Estrellas (GitHub) |
|---|---|---|
| tonone-ai | tonone-ai/tonone | 77 |
Qué contiene el paquete
Tal como se publica en Community GitHub marketplaces.
Skills: 3
deploy-canarydeploy-recondeploy-serve
Agentes: 1
deploy
Qué cambió
- Pasó a ser un producto que seguimos
- Community GitHub marketplaces: apareció
Plugins similares
Productos cuyos propios nombres, descripciones, herramientas y skills son los más cercanos a este por su significado, en todos los marketplaces que leemos. La cercanía se ordena solo dentro de esta lista.
-
Deploy ML models with FastAPI, Docker, Kubernetes. Use for serving predictions, containerization, monitoring, drift detection, or encountering latency issues, health check…
-
do-machine-learning-engineering
ML engineering agents providing expertise in MLOps, model deployment, and inference optimization
-
Search, rank and compare open-source AI projects with Archestack's open data
-
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
-
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
-
AI Operations Team — 9 agents: Deploy, Eval, Trace, Guard, Budget, Token, Prompt, Embed, Rank
-
Practical AI/ML implementation, LLM integration, and intelligent automation for production applications
-
Build, train, and deploy AI models with deep AWS AI/ML expertise brought directly into your coding assistants, covering the surface area of Amazon SageMaker AI.
-
ML/AI engineer — model training, MLOps, feature engineering, LLM integration
-
ML engineering agents providing expertise in MLOps, model deployment, and inference optimization
Plugins similares por marketplace
La misma pregunta a cada marketplace por separado: ¿hay allí un equivalente de este plugin?
Publicado en Claude Code: claude-plugins-community (5)
-
Build, run, and monitor AI/ML workflows on Jetty — from prompt to production in 5 minutes.
-
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
-
Claude model selection advisor — recommends optimal model for each task via shell hook. Zero attack surface.
-
DataRobot Agent Skills - Agentic skills for DataRobot enterprise AI and ML workflows. Covers model training, deployment, predictions, feature engineering, monitoring…
-
Multi-agent AI pipelines with structural write/review isolation, crash-safe state recovery, and spec-driven development. Run sequential, parallel fan-out, iterative-loop, or…
Publicado en Claude Code: claude-plugins-official (5)
-
Build, train, and deploy AI models with deep AWS AI/ML expertise brought directly into your coding assistants, covering the surface area of Amazon SageMaker AI.
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
-
Skills for tracing, evaluating, and improving AI agents with MLflow. Supports the full agent improvement loop: instrument → trace → evaluate → iterate → validate.
-
Build, train, evaluate, and use open source AI models, datasets, and spaces.
Publicado en Claude: knowledge-work-plugins (5)
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Deploy, debug, and monitor applications on Render. Includes skills, an agent, slash commands, and a render.yaml validation hook.
-
Official Buildkite skills for Claude Code, Cursor, and other AI coding agents — pipelines, migration, preflight, agent runtime, CLI, and API
Publicado en Codex: openai-curated (openai/plugins) (5)
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Cloudflare platform plugin with curated skills for Workers, Wrangler, and Agents SDK plus the official Cloudflare API MCP server.
-
Comprehensive skill for the entire Temporal lifecycle — developing applications, using the Temporal CLI, running and managing Temporal Server, and working with Temporal Cloud.
Publicado en Community GitHub marketplaces (5)
-
Deploy ML models with FastAPI, Docker, Kubernetes. Use for serving predictions, containerization, monitoring, drift detection, or encountering latency issues, health check…
-
do-machine-learning-engineering
ML engineering agents providing expertise in MLOps, model deployment, and inference optimization
-
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
-
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
-
AI Operations Team — 9 agents: Deploy, Eval, Trace, Guard, Budget, Token, Prompt, Embed, Rank
Publicado en Copilot CLI: github/awesome-copilot (5)
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Model, visualize, and deploy applications with Radius from the GitHub Copilot app and CLI.
-
Skills and interactive Copilot canvas for designing, configuring, testing and deploying agents to Microsoft Foundry.
-
Transform Claude into an Azure expert. This plugin integrates the Azure MCP server and specialized Azure skills to move beyond generic advice. It enables Claude to perform…
-
Use Datadog directly in Copilot / VS Code through a preconfigured Datadog MCP server. Query logs, metrics, traces, dashboards, and more through natural conversation.
Publicado en Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
-
Bring Azure DevOps work-item, repository, and pull-request workflows into GitHub Copilot.
-
code-apps-preview
Build and deploy Power Apps code apps using React, Vite, and Power Platform connectors.
Publicado en Cursor: cursor/plugins (5)
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
-
Skills for building on the Cursor Origin API. Fetch the live spec first, then follow the Origin rules for credentials, scopes, webhooks, paging, and errors. Includes a skill that…
-
Build apps, scripts, and automations with the TypeScript SDK.
-
Ask Databricks Genie questions about your workspace's data in plain language.
-
if you want to go fast, go deep first. pstack helps you write less, but higher quality code. rigorous agent workflows you can parallelize with confidence.
Publicado en Docker MCP Catalog (5)
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
-
Seamless interaction with Novita AI platform resources.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Giving Claude ability to run code with E2B via MCP (Model Context Protocol).
-
Give your AI agents trusted access to the full Postman platform.
Publicado en Official MCP Registry (5)
-
Search, rank and compare open-source AI projects with Archestack's open data
-
replicate com.mcparmory/replicate
Run AI models, create deployments, and manage predictions via cloud API
-
Discover, run, inspect, build, test, and privately reuse AI workflows.
-
Train, track and query models on a running dashAI instance. Read-oriented, no delete tools.
-
Onde Inference CLI: Fine-tune & Deploy Local LLMs
MCP server to fine-tune LoRA, export GGUF, and deploy local LLMs on Onde Inference.
Publicado en PyPI (MCP servers) (5)
-
Hanzo MCP Server - Unified tool surface with AI, cloud control, vector search, and multi-framework UI
-
lineai-mcp-server io.github.lineai-intelligence/lineai-mcp-server
An MCP Server to utilize Lineai's rich software dependency data in your AI programming assistant.
-
awslabs.aws-bedrock-custom-model-import-mcp-server
An AWS Labs Model Context Protocol (MCP) server for Bedrock Custom Model Import
-
Every tool your AI needs in one self-hosted install: memory, reasoning, git, Docker and more.
-
offline-mcp io.github.gabrielmahia/offline-mcp
Local AI over Ollama for low connectivity: status, local inference, model and deployment guides.
Publicado en npm registry (MCP servers) (5)
-
13 years of Microsoft hyperscale engineering, packaged as a harness for your AI coding agent.
-
Hanzo MCP Server - Unified tool surface with AI, cloud control, vector search, and multi-framework UI
-
Deploy and manage apps on your own AppCrane instance, the self-hosted PaaS for AI-built apps.
-
Intelligent CLI tool with AI-powered model selection that analyzes your hardware and recommends optimal LLM models for your system
-
Live AWS, database & Kafka infrastructure context for AI coding assistants via MCP.
Encontrados por significado, no por código ni repositorio compartidos: los plugins similares siguen siendo productos distintos, y esto no es una reseña ni una recomendación.
¿Quieres esta marca para tu plugin en nuestro catálogo?
Demuestra que lo mantienes con un archivo en su repositorio, un archivo en tu dominio o un registro DNS, y podrás mostrar esta marca en la ficha, con banners en vivo para tu web y tu README. Cómo funciona la verificación
Además recibirás avisos cuando un marketplace lo publique, lo retire, cambie su marca verificada o lo que pide, y su endpoint remoto quedará monitorizado como un servicio web.
Datos de Community GitHub marketplaces. Las cifras proceden de nuestros propios recorridos periódicos por los marketplaces, leída por última vez el . No publicamos datos de contacto de los editores de plugins.