jungle-grid-mcp-server
Jungle Grid MCP Server lets AI agents submit, estimate, monitor, and retrieve logs for GPU workloads through Jungle Grid. It enables agentic execution for inference, training, fine-tuning, and batch jobs without manually choosing GPU providers or infrastructure.
README
Jungle Grid MCP Server
Run Jungle Grid GPU workloads from MCP-aware AI hosts such as Claude Desktop, Cursor, Windsurf, and MCP Inspector.
The server runs locally over stdio and forwards tool calls to the Jungle Grid REST API with your API key.
Requirements
- Node.js 18 or newer
- A Jungle Grid API key
- Optional:
JUNGLE_GRID_API_URLfor a self-hosted orchestrator
For the full submit workflow, the API key needs jobs:write. That scope allows
estimate, submit, polling, cancellation, and logs for jobs owned by the key's
account. list_jobs still requires jobs:read.
Quick Start
JUNGLE_GRID_API_KEY=jg_... npx -y @jungle-grid/mcp
On Windows PowerShell:
$env:JUNGLE_GRID_API_KEY = "jg_..."
npx -y @jungle-grid/mcp
The server uses stdio, so a successful manual launch appears to wait for MCP
messages. If JUNGLE_GRID_API_KEY is missing, it exits with a clear error.
Claude Desktop
Add this to claude_desktop_config.json, then fully restart Claude Desktop.
{
"mcpServers": {
"junglegrid": {
"command": "npx",
"args": ["-y", "@jungle-grid/mcp"],
"env": {
"JUNGLE_GRID_API_KEY": "jg_..."
}
}
}
}
Windows config path:
%APPDATA%\Claude\claude_desktop_config.json
macOS config path:
~/Library/Application Support/Claude/claude_desktop_config.json
Cursor or Project MCP Config
For a checked-in project config, avoid committing secrets. Put the API key in the environment used to launch Cursor and keep the config secret-free.
{
"mcpServers": {
"junglegrid": {
"command": "npx",
"args": ["-y", "@jungle-grid/mcp"]
}
}
}
For a local, uncommitted config, you can include the key directly:
{
"mcpServers": {
"junglegrid": {
"command": "npx",
"args": ["-y", "@jungle-grid/mcp"],
"env": {
"JUNGLE_GRID_API_KEY": "jg_..."
}
}
}
}
Self-Hosted Orchestrator
JUNGLE_GRID_API_URL defaults to
https://api.junglegrid.dev. Override it when your host should
call a different orchestrator.
{
"mcpServers": {
"junglegrid": {
"command": "npx",
"args": ["-y", "@jungle-grid/mcp"],
"env": {
"JUNGLE_GRID_API_KEY": "jg_...",
"JUNGLE_GRID_API_URL": "https://your-orchestrator.example.com"
}
}
}
}
Tools
estimate_job: estimate GPU tier, region, duration, and credit cost.submit_job: submit an asynchronous GPU workload with optionalenvironmentvalues.get_job: fetch current job status and details.list_jobs: list recent jobs for the authenticated account.cancel_job: cancel a pending, queued, or running job.get_job_logs: fetch stdout, stderr, and exit information.stream_job_logs: stream live logs until completion or timeout.list_job_artifacts: list managed artifacts uploaded for a job.get_artifact_download_url: create a signed download URL for one managed artifact.
Real-Time Job Pattern
Use submit_job to start work, stream_job_logs for live output, then
list_job_artifacts after completion to retrieve saved files.
{
"command": ["python", "-c", "import os; exec(os.environ['CODE'])"],
"environment": {
"CODE": "import os, json\nos.makedirs('/workspace/artifacts', exist_ok=True)\nwith open('/workspace/artifacts/output.json','w') as f:\n json.dump({'status':'ok'}, f)"
}
}
This is the recommended pattern when the real Python payload is too long to fit
comfortably in the command array.
For managed jobs, Jungle Grid automatically creates /workspace/artifacts and
uploads any regular files written there. Users do not need to create signed
upload URLs or call artifact completion endpoints manually.
Local Development
npm install
npm run build
JUNGLE_GRID_API_KEY=jg_... node dist/index.js
Inspect the server with MCP Inspector:
JUNGLE_GRID_API_KEY=jg_... npx @modelcontextprotocol/inspector node dist/index.js
Publishing
Verify the package before publishing:
npm run build
npm pack --dry-run
Publish the scoped package publicly:
npm publish --access public
Troubleshooting
JUNGLE_GRID_API_KEY environment variable is required: add the key to the host configenvblock or to the environment that launches the host.- Tools do not appear: fully quit and reopen the MCP host after editing config.
- Old package version: pin a version in config, for example
["@jungle-grid/mcp@0.1.0"], or clear the npx cache. - API calls fail: confirm the key is valid and
JUNGLE_GRID_API_URLpoints to the orchestrator you intend to use.
Contributors wanted
We are opening up the Jungle Grid MCP server for contributors interested in AI agents, MCP, developer tools, and workload execution.
Good first areas:
- Improve docs
- Add example prompts
- Add tests for MCP tool handlers
- Add Docker support
- Improve GitHub Actions
- Build integration examples
Start with issues labeled good first issue.
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