
Digitalocean Agentic Cloud
- 218 installs
- 63 repo stars
- Updated July 18, 2026
- bobmatnyc/claude-mpm-skills
Deploy and configure agent workloads on DigitalOcean agentic cloud—compute, networking, and services—when moving prototypes to a hosted production environment.
About
digitalocean-agentic-cloud from bobmatnyc/claude-mpm-skills guides deployment of agentic applications onto DigitalOcean's cloud stack. It covers provisioning, networking, and service setup so Claude agent prototypes become reachable, maintainable production workloads rather than local-only experiments.
- DigitalOcean agent hosting
- Cloud provisioning guidance
- Agent endpoint deployment
- Scalable agent infrastructure
- Production readiness on DO
Digitalocean Agentic Cloud by the numbers
- 218 all-time installs (skills.sh)
- Ranked #448 of 1,039 Cloud & Infrastructure skills by installs in the Skillselion catalog
- Data as of Aug 1, 2026 (Skillselion catalog sync)
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| Installs | 218 |
|---|---|
| repo stars | ★ 63 |
| Last updated | July 18, 2026 |
| Repository | bobmatnyc/claude-mpm-skills ↗ |
What it does
Deploy and configure agent workloads on DigitalOcean agentic cloud—compute, networking, and services—when moving prototypes to a hosted production environment.
Files
DigitalOcean Agentic Cloud Skill
--- progressive_disclosure: entry_point: summary: "Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents with GPU infrastructure, knowledge bases, and agent routes." when_to_use:
- "When building or deploying AI agents on DigitalOcean"
- "When selecting Gradient AI for GPU-backed inference"
- "When designing agent workflows with knowledge bases and routes"
quick_start:
- "Choose Gradient AI Agentic Cloud or Gradient AI Platform"
- "Select foundation models and GPU resources"
- "Attach knowledge bases and define agent routes"
- "Deploy agents and monitor usage"
token_estimate: entry: 90-110 full: 3000-4200 ---
Overview
DigitalOcean Gradient AI provides managed infrastructure for building and deploying AI agents. Use Agentic Cloud for end-to-end agent workflows and the AI Platform for GPU-powered agent deployment.
Gradient AI Agentic Cloud
- Build, train, and deploy AI agents on managed infrastructure.
- Use managed resources to run agent workloads without manual GPU orchestration.
Gradient AI Platform
- Use GPU-powered infrastructure for AI agents and inference.
- Combine foundation models with knowledge bases.
- Configure agent routes to direct traffic and workflows.
Agent Workflow
- Select the target model and compute profile.
- Prepare datasets and knowledge bases.
- Define agent routes and inference behavior.
- Deploy agents and observe runtime metrics.
Integration Considerations
- Use object or block storage for datasets and artifacts.
- Align deployment with VPC and access controls.
- Track costs and usage in projects.
Complementary Skills
When using this skill, consider these related skills (if deployed):
- digitalocean-storage: Spaces, Volumes, and NFS for datasets.
- digitalocean-compute: GPU Droplets or Kubernetes for adjacent workloads.
- digitalocean-management: Monitoring and project organization.
Note: Complementary skills are optional. This skill is fully functional without them.
Resources
DigitalOcean Docs:
- Gradient AI Agentic Cloud: https://docs.digitalocean.com/products/gradient-ai-agentic-cloud/
- Gradient AI Platform: https://docs.digitalocean.com/products/gradient-ai-platform/
{
"name": "digitalocean-agentic-cloud",
"version": "1.0.0",
"category": "toolchain",
"toolchain": null,
"tags": [
"digitalocean",
"gradient-ai",
"agentic-cloud",
"ai",
"gpu",
"agents"
],
"entry_point_tokens": 100,
"full_tokens": 630,
"related_skills": [
"digitalocean-storage",
"digitalocean-compute",
"digitalocean-management"
],
"author": "Claude MPM",
"license": "MIT",
"platform": "deployment"
}