Cloud World Model on Smithery
    For AI agents & builders
    Infrastructure & platform teams · architects
    Patent Pending

    Simulate the Cloud
    Without the Cloud

    Give agents a world model for infrastructure — predict cost, latency, errors, and resilience across AWS, GCP, Azure, OCI, and DigitalOcean before deploying or changing infrastructure.

    Latency
    Modeled
    Error rate
    Modeled
    Cost / hour
    Estimated
    Resilience
    Failure-tested
    Run a simulation

    1,000 free credits every 30 days; no card required.

    Connect via MCP

    Compare modeled outcomes for cost/hr, latency, error rate, and resilience before deploying or changing infrastructure.

    architecture.simulation
    Running
    Edge
    Load Balancer
    Traffic10k RPS
    Compute
    Autoscaling Pool
    Capacity3 nodes
    Data
    Managed Database
    StateHealthy
    AWS · GCP · Azure · OCI · DigitalOcean
    PRE-PROVISION DECISION SUPPORT
    No real cloud provisioning
    Zero Infrastructure Costs
    Instant Setup
    Agent & Headless Ready
    Measured evidence, stated limits

    See what the simulation is measured against

    Our accuracy benchmark compares simulated results with an owned AWS load-test campaign at 10, 100, 500, and 1,000 requests per second. Cost is compared against the public price list; other providers use documentation references, not the same owned measurement. Scores describe this benchmark architecture, not a guarantee for every workload.

    Featured & Recognized

    Product Hunt daily top-post badge for Cloud World Model

    See It In Action

    Watch how Cloud World Model simulates real cloud infrastructure behavior — without provisioning a single resource.

    Recorded simulation run Demo

    World Model Capabilities

    Advanced AI models predict infrastructure behavior with physics-informed constraints and learned dynamics

    01
    Real-time Simulation
    Predict latency, throughput, and cost with physics-informed AI models
    02
    Failure Injection
    Test resilience with AZ outages, traffic spikes, and node failures
    03
    Cost Optimization
    Train RL agents to minimize costs while maintaining performance
    04
    Multi-Cloud Support
    Simulate AWS, GCP, Azure, OCI, and DigitalOcean with provider-specific behavior
    Supports x402
    Linux Foundation Protocol
    AI agents can call any API endpoint without signing up — pay per call in USDC on Base. No account, no API key required.

    Network

    Base (Ethereum L2)

    Asset

    USDC

    Discovery

    /api/billing/x402/config

    Agent Storefront on TryPoncho

    For AI Agents

    The Cloud World Model merchant page on TryPoncho lists all x402-priced endpoints, live pricing, the curated OpenAPI spec, and AgentCash integration — a single machine-readable index for autonomous agents discovering this API.

    Open Agent Storefront

    Connect via MCP

    For AI Assistants

    Use Smithery or paste the hosted HTTP URL into Claude, Cursor, Windsurf, or any MCP-compatible client — no local install required.

    What Engineers Are Saying

    Engineers and leaders reacting to the launch on Product Hunt and LinkedIn

    Simulation lets teams explore ideas before committing resources. Finding weaknesses before deployment is almost always less expensive than discovering them in production.

    Gennadiy Vaksman

    Technology & Business Leader / Advisor

    From LinkedIn ↗

    Cloud mistakes usually get expensive after you already deployed them. Being able to play with failure scenarios, cost, and scaling before touching real infra feels especially useful for learners and small teams that don't have a proper staging setup.

    Cost avoidance during cloud experimentation has always been a silent constraint in engineering teams. Digital twin style environments change exploration economics in a meaningful way.

    Paul Storm

    Co-Founder, Dr. Storm Advisory GmbH

    From LinkedIn ↗

    Cost is the question that never really leaves the room, and almost always the hardest thing to pin down before you commit.

    Chaos engineering with resilience scoring before touching real infra is a great fit for teams that want to test failure modes without blowing a staging budget.

    If simulation becomes reliable enough, it could seriously change how teams approach pre-production testing.

    Thomas Hoon

    China-ASEAN Market Entry Strategist

    From LinkedIn ↗

    My 'test' is deploy-and-pray, no real staging. The failures that hurt are the silent ones, not the loud ones.

    Ready to Start Simulating?

    Build, test, and optimize cloud architectures without the risk or cost