Jetty — AI/ML Workflows for Any Agent

Build, run, and monitor AI/ML workflows on Jetty from any AI coding tool. Works with Claude Code, Cursor, VS Code Copilot, Windsurf, Zed, Gemini CLI, Codex CLI, and any MCP-compatible agent.

Quick Start (Claude Code)

claude plugin marketplace add jettyio/agent-skill
claude plugin install jetty@jetty

Then run /jetty-setup to create an account, configure your API key, and run your first workflow in under 5 minutes.

Install in Your Tool

Jetty uses the Model Context Protocol (MCP) to connect to your agent. Pick your tool below.

Claude Code

Plugin (recommended) — includes guided setup wizard, workflow skills, and MCP tools:

claude plugin marketplace add jettyio/agent-skill
claude plugin install jetty@jetty

Then run /jetty-setup to get started interactively.

MCP server only:

claude mcp add jetty -- npx -y jetty-mcp-server

Or add to your project's .mcp.json:

{
  "mcpServers": {
    "jetty": {
      "command": "npx",
      "args": ["-y", "jetty-mcp-server"],
      "env": { "JETTY_API_TOKEN": "mlc_your_token" }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "jetty": {
      "command": "npx",
      "args": ["-y", "jetty-mcp-server"],
      "env": { "JETTY_API_TOKEN": "mlc_your_token" }
    }
  }
}

VS Code Copilot

Add to .vscode/mcp.json in your project root:

{
  "servers": {
    "jetty": {
      "command": "npx",
      "args": ["-y", "jetty-mcp-server"],
      "env": { "JETTY_API_TOKEN": "mlc_your_token" }
    }
  }
}

Or run MCP: Add Server from the Command Palette.

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "jetty": {
      "command": "npx",
      "args": ["-y", "jetty-mcp-server"],
      "env": { "JETTY_API_TOKEN": "mlc_your_token" }
    }
  }
}

Zed

Add to your Zed settings (~/.config/zed/settings.json):

{
  "context_servers": {
    "jetty": {
      "command": {
        "path": "npx",
        "args": ["-y", "jetty-mcp-server"],
        "env": { "JETTY_API_TOKEN": "mlc_your_token" }
      }
    }
  }
}

Gemini CLI

gemini extensions install https://github.com/jettyio/agent-skill

During installation, you'll be prompted for your Jetty API token. The extension registers the MCP server and loads context automatically.

To install from a local clone instead:

gemini extensions install --path /path/to/agent-skill

Codex CLI

Add to ~/.codex/config.json:

{
  "mcpServers": {
    "jetty": {
      "command": "npx",
      "args": ["-y", "jetty-mcp-server"],
      "env": { "JETTY_API_TOKEN": "mlc_your_token" }
    }
  }
}

Any Other MCP Client

JETTY_API_TOKEN=mlc_your_token npx -y jetty-mcp-server

The server communicates over stdio using the MCP protocol.

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Get Your API Token

1. Sign up at flows.jetty.io
2. Go to Settings → API Tokens
3. Create a token (starts with mlc_)
4. Add it to your tool's config as shown above

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First-Time Setup

Once connected, ask your agent to help you get started. This works in any MCP-connected tool — just paste the prompt below into your agent's chat:

Set up Jetty for me. List my collections, then deploy the cute-feline-detector demo workflow using the create-task tool with this workflow JSON. Then run it with run-workflow using the prompt "a fluffy orange tabby cat sitting in a sunbeam". Poll list-trajectories until it completes, then show me the results with get-trajectory.

Before running the demo, store your AI provider key in your collection's environment variables. Ask your agent:

Use the Jetty get-collection tool to check my collection's environment variables. I need to add my OpenAI API key (or Gemini API key) so workflows can use it.

Claude Code users: Just run /jetty-setup instead — the guided wizard handles all of this automatically.

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Available MCP Tools

Once connected, your agent has access to 14 tools:

Tool	Description
list-collections	List all collections (workspaces)
get-collection	Get collection details and environment variable keys
list-tasks	List tasks (workflows) in a collection
get-task	Get task details and workflow definition
create-task	Create a new task with a workflow
update-task	Update a task's workflow or description
run-workflow	Run a workflow asynchronously
run-workflow-sync	Run a workflow synchronously (blocks until done)
list-trajectories	List recent workflow runs
get-trajectory	Get full run details with step outputs
get-stats	Get execution statistics
add-label	Label a trajectory (e.g., quality=high)
list-step-templates	List available step templates
get-step-template	Get template details and schema

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Claude Code Skills

The plugin adds two skills for richer Claude Code integration:

/jetty-setup — Guided Onboarding

Interactive wizard that handles account creation, API key storage, provider selection (OpenAI or Gemini), and runs a demo workflow — all in under 5 minutes.

/jetty — Natural Language Workflow Management

/jetty list collections
/jetty list tasks in my-project
/jetty run my-project/my-task with prompt="Hello, world!"
/jetty show the last trajectory for my-project/my-task
/jetty create a task called test-echo in my-project using text_echo
/jetty add label quality=high to trajectory abc123 in my-project/my-task

---

Workflow Templates

Ready-to-use templates are in skills/jetty/templates/:

Template	Description
cute-feline-detector-openai	Prompt → DALL-E 3 image → GPT-4o cuteness judge
cute-feline-detector-gemini	Prompt → Gemini image → Gemini Flash cuteness judge
simple-chat	Basic LLM chat with system prompt
model-comparison	Compare two LLM responses with an AI judge
image-generation	Text-to-image with Replicate/FLUX
batch-processor	Fan-out parallel processing
document-summarizer	Configurable document summarization

Use the create-task MCP tool to deploy any template to your collection.

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Shell Functions (Standalone CLI)

For direct terminal usage without any AI tool:

export JETTY_API_TOKEN="mlc_your_token_here"
source path/to/skills/jetty/jetty-cli.sh

jetty_health                                    # Check connectivity
jetty_collections                               # List collections
jetty_run_sync my-project my-task '{"prompt": "Hello"}'  # Run a workflow
jetty_trajectories my-project my-task           # View execution history
jetty_help                                      # Full command reference

---

How It Works

Jetty runs AI/ML workflows defined as JSON pipelines. Each workflow has:

• init_params — Input parameters (e.g., a prompt)
• step_configs — Pipeline steps (e.g., LLM call → image generation → judge)
• steps — Execution order

Results are stored as trajectories with full step-by-step outputs, downloadable files, and labeling support.

Platform

Service	URL	Purpose
Flows API	flows-api.jetty.io	Run workflows, trajectories, files
Dock API	dock.jetty.io	Collections, tasks, datasets
Web UI	flows.jetty.io	Dashboard and management

Prerequisites

• Node.js 18+ (for the MCP server via npx)
• A Jetty API token (get one here)
• An OpenAI or Google Gemini API key (for image generation workflows)

Documentation

• AI Tool Integrations
• API Reference
• Workflow Building Guide
• Known Gotchas

Troubleshooting

Problem	Solution
"Invalid or expired token"	Regenerate at flows.jetty.io → Settings → API Tokens
"Access denied"	Verify your token has access to the collection
MCP tools not showing up	Restart your editor/agent after config changes
Workflow fails	Use get-trajectory to inspect step-by-step outputs
/jetty-setup not found	Claude Code only — reinstall: claude plugin marketplace add jettyio/agent-skill && claude plugin install jetty@jetty

License

MIT — see LICENSE for details.