deploy
AI Operations Team — Deploy: Model serving, inference APIs, blue/green deploys, rollback, and canary releases for production ML.
Lot de plugins · par tonone-ai
Aperçu
deploy est un lot de plugins pour les outils de code IA publié par tonone-ai. Places de marché que nous lisons et qui le référencent : 1 (Community GitHub marketplaces). Nous l'avons vu pour la première fois le 2026-11-09 et n'avons enregistré aucun changement depuis. Selon notre passage sur les places de marché du 2026-11-09.
Ce qu'il demande
- S'installe comme lot de plugins
Aucune des places de marché que nous lisons ne publie ses outils ni les réglages qu'il demande.
Ce qu'il déclare, demande et exécute, en détail
N’installez que des plugins de développeurs en qui vous avez confiance. Nous reprenons ce que publient les places de marché et ne testons pas les plugins.
Fonctionne avec
- Claude Code
D'après les marketplaces qui le listent et le transport MCP qu'il déclare, tels que chaque client les documente. Nous ne testons pas les plugins.
Connecter
Commandes et configurations construites uniquement à partir de ce que déclarent ses places de marché. Nous ne les exécutons pas pour vous et ne testons pas les plugins.
En plugin Claude Code
Construit à partir de ce que déclare Community GitHub marketplaces.
/plugin marketplace add tonone-ai/tonone
/plugin install deploy@tonone-ai
Où il est publié
| Place de marché | Statut | Version | Chiffres | Vérifié | Vu pour la première fois |
|---|---|---|---|---|---|
| Place de marché communautaire tonone-ai/tonone (Ouvrir la source sur GitHub) | Référencé | 1.19.0 | Aucun chiffre publié | Non marqué |
Chaque chiffre est celui de la place de marché et n'est jamais additionné entre places de marché. Une place de marché qui ne publie pas de chiffre n'en affiche aucun : pas de nombre ne veut pas dire zéro.
Listé dans une place de marché communautaire
| Place de marché | Dépôt | Étoiles (GitHub) |
|---|---|---|
| tonone-ai | tonone-ai/tonone | 77 |
Quelles places de marché nous lisons et comment nous les vérifions
Ce que contient le lot
Tel que publié sur Community GitHub marketplaces.
Skills: 3
deploy-canarydeploy-recondeploy-serve
Agents: 1
deploy
Ce qui a changé
- Est devenu un produit que nous suivons
- Community GitHub marketplaces: apparu
Plugins similaires
Produits dont les noms, descriptions, outils et skills sont les plus proches de celui-ci par le sens, sur toutes les places de marché que nous lisons. La proximité n'est classée qu'à l'intérieur de cette liste.
-
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 similaires par place de marché
La même question posée à chaque place de marché séparément : y a-t-il là un équivalent de ce plugin ?
Référencé sur 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…
Référencé sur 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.
Référencé sur 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
Référencé sur 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.
Référencé sur 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
Référencé sur 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.
Référencé sur 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.
Référencé sur 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.
Référencé sur 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.
Référencé sur 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.
Référencé sur 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.
Référencé sur 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.
Trouvés par le sens, et non par un code ou un dépôt commun : les plugins similaires restent des produits distincts, et ceci n'est ni un avis ni une recommandation.
Vous voulez cette marque pour votre plugin dans notre catalogue ?
Prouvez que vous le maintenez avec un fichier dans son dépôt, un fichier sur votre domaine ou un enregistrement DNS, et vous pourrez afficher cette marque sur la fiche, avec des bannières à jour pour votre site et votre README. Comment se passe la vérification
Vous recevez aussi des alertes quand une marketplace le publie, le retire, change sa marque vérifiée ou ce qu'il demande, et son endpoint distant est surveillé comme un service web.
Données issues de Community GitHub marketplaces. Les chiffres proviennent de nos propres passages réguliers sur les places de marché, dernière lecture le . Nous ne publions aucune coordonnée des éditeurs de plugins.