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Jungle Grid

The execution layer for AI workloads and agents. Run inference, training, fine-tuning, and batch jobs without managing GPUs.
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Jungle Grid

The execution layer for AI workloads and agents.

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Jungle Grid lets developers and AI agents run inference, training, fine-tuning, and batch workloads without manually managing GPUs, regions, providers, pods, or infrastructure settings.

Submit workload intent. Jungle Grid handles placement, routing, execution, lifecycle tracking, logs, retries and recovery, and artifact retrieval across available GPU capacity.

What Jungle Grid Does

Jungle Grid turns AI workload intent into managed execution:

  • Classifies workload type and execution requirements.
  • Routes jobs across available GPU capacity.
  • Tracks job state, logs, failures, retries, and artifacts.
  • Gives developers one control plane across portal, CLI, API, and MCP entry points.
Intent -> Routing -> GPU placement -> Execution -> Logs -> Artifacts

Built For Developers And Agents

Jungle Grid is designed for teams building systems that need real compute without exposing every infrastructure decision to the caller.

  • Developers can submit and monitor jobs without becoming GPU operations engineers.
  • AI agents can estimate, launch, inspect, cancel, and retrieve results from workload runs.
  • Internal tools can connect to a workload execution layer instead of directly managing provider-specific GPU primitives.

Ways To Use Jungle Grid

Surface Use it for
Portal Submit workloads, inspect jobs, review logs, and retrieve outputs from the web.
CLI Run and automate jobs from local development, CI, and terminal workflows.
API Integrate Jungle Grid into products, internal platforms, and backend services.
MCP Give AI agents a controlled interface for estimating, submitting, tracking, and cancelling workloads.

Open Source And MCP

MCP is one major integration surface for Jungle Grid, enabling agent-facing compute workflows through MCP-compatible clients.

  • Jungle Grid MCP Server exposes tools for estimating, submitting, tracking, cancelling, reading logs, and retrieving artifacts.
  • The hosted MCP endpoint connects agent workflows to the Jungle Grid API while keeping scheduling, routing, billing, and artifact storage in the platform layer.

Get Started

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  1. forgegrid forgegrid Public

    TypeScript

  2. mcp-server mcp-server Public

    MCP server for Jungle Grid lets agents submit, monitor, and retrieve logs from AI workloads.

    TypeScript 1

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