Is Smoke Monkey an AI model?

No. Smoke Monkey is not an LLM. It is an embeddable, framework-agnostic runtime that turns LLMs (NVIDIA, Gemini, OpenAI, Claude, Ollama) into autonomous engineering agents capable of multi-step planning, calling tools, editing files, and running test loops with zero runtime dependencies.

Do I need a database (Postgres, SQLite, or Redis)?

No database is required. State is persisted through lean session files on disk, or you can plug in your own custom storage adapter. You can deploy it as a CLI, a desktop app, or inside a serverless function without provisioning a database.

How does human-in-the-loop permission gating work?

Smoke Monkey comes with three permission policies: allow-all, deny-all, and ask-default (or a custom function resolver). When a sensitive tool like edit_file or run_command is called under "ask", the runtime emits a permission.required event, pausing execution until your code or UI calls agent.resolvePermission(id, "allow" | "deny").

How does the Model Context Protocol (MCP) server work?

Smoke Monkey ships an official stdio MCP server in smoke-monkey-harness-mcp. Point Claude Code, Cursor, Codex, or opencode at it using npx -y smoke-monkey-harness-mcp to let other AI tools plan, scaffold, verify, and run agents using Smoke Monkey automatically.

What are SKILL.md skills and how do they prevent context bloat?

Skills are directories containing a SKILL.md workflow file. The system prompt only includes a one-line catalog of available skills. When a task requires specialized expertise (e.g. frontend-ui-engineering, test-driven-development, or security-hardening), the agent calls use_skill to load instructions just-in-time, saving thousands of tokens.

What is an AI Agent Harness?

An AI agent harness is the execution environment that bridges raw Large Language Models (LLMs) to real-world software engineering capabilities. While an LLM generates tokens, an AI harness manages deterministic phase loops (explore, plan, edit, verify, recover), tool execution sandboxing, token budget compaction, and safety gates needed for autonomous problem-solving.

What makes Smoke Monkey an Agentic AI runtime rather than a simple wrapper?

Unlike basic prompt-response chains, Smoke Monkey implements true agentic AI architecture: a deterministic 6-phase state machine with automatic failure recovery, runaway loop guards, 24 built-in developer tools, dynamic subcontext isolation, and interactive human-in-the-loop permission pauses.

Is Smoke Monkey Harness 100% Open Source AI?

Yes. Smoke Monkey Harness is 100% open source under the permissive MIT license with zero runtime dependencies. There is no telemetry lock-in, no mandatory cloud backend, and no database requirement—giving engineering teams complete sovereignty over their agent code.

What Agent APIs does Smoke Monkey Harness provide?

Smoke Monkey provides composable TypeScript Agent APIs: createAgent() for initialization, agent.run() for multi-turn execution, agent.on() for fine-grained lifecycle and streaming events, agent.resolvePermission() for interactive human authorization, subcontext switching APIs, and stdio Model Context Protocol (MCP) server endpoints.

Can I run completely offline without API keys?

Yes! Smoke Monkey natively supports Ollama out of the box. Set provider: "ollama" and model: "qwen3:8b" with workspacePath, and the agent will run locally on your machine with zero external network requests.

Smoke Monkey vs Google Agent Development Kit (ADK)

Google Cloud Agent FrameworkUpdated: October 2026

Google Agent Development Kit (ADK) Alternative: Multi-Model Open Source Harness

Google's ADK primarily optimizes for Gemini models and Google Cloud infrastructure. Smoke Monkey Harness supports Gemini as one of many providers while running on any Node.js infrastructure.

Comparative Benchmark: Smoke Monkey Harness TypeScript vs Google Agent Development Kit (ADK)

|Verified for Node.js 18+ & Bun|100% MIT Open Source

The Executive Verdict (Quick Answer)

Why choose Smoke Monkey over Google Agent Development Kit (ADK)? Choose Smoke Monkey if you need Gemini support alongside Claude, GPT-4o, and local Ollama—with no Google Cloud billing account required.

Why Developers Switch from Google Agent Development Kit (ADK) to Smoke Monkey

Provider Agnostic: Use Gemini today, switch to Claude or NVIDIA tomorrow with one config line.

No Google Cloud Lock-In: Run locally, on AWS, Azure, or any Node.js deployment target.

Native MCP: Built-in stdio Model Context Protocol for IDE and tool integration.

Zero Cost at Rest: No Google Cloud credits needed for development and testing.

Detailed Feature-by-Feature Matrix

Direct side-by-side comparison of core runtime capabilities and architectural trade-offs.

Capability	Smoke Monkey Harness	Google Agent Development Kit (ADK)	Key Architectural Difference
Primary Model Support	✅ Gemini, Claude, OpenAI, NVIDIA, Ollama	⚠️ Optimized for Gemini / Vertex AI	No vendor preference built into the execution engine.
Deployment Target	✅ Local, serverless, any cloud, Electron	⚠️ Optimized for Google Cloud Run and Vertex	Runs anywhere Node.js 18+ is available.

Code Implementation Comparison

Configuring a Gemini-Powered Agent

Smoke Monkey (TypeScript)Zero Dependencies

gemini-agent.tstypescript

1import { createAgent } from 'smoke-monkey-harness';
2
3// Use Gemini today, swap to Claude anytime
4const agent = createAgent({
5  provider: 'gemini',
6  model: 'gemini-1.5-pro',
7  apiKey: process.env.GEMINI_API_KEY,
8  workspacePath: process.cwd(),
9});
10
11await agent.run('Scan for memory leaks in async handlers');

Google Agent Development Kit (ADK)Google Cloud Tied

google_adk_agent.pypython

1from google.adk.agents import Agent
2
3root_agent = Agent(
4    name='code_agent',
5    model='gemini-2.0-flash',
6    instruction='You are a software engineer.',
7    tools=[],
8)
9# Requires Google Cloud / Vertex AI credentials and billing

Architecture Note: Smoke Monkey gives you full Gemini access with zero Google Cloud billing requirements in development.

Running Gemini with Full Privacy in Development

With Smoke Monkey, you can use Gemini for cloud-scale tasks and seamlessly switch to Ollama for local development iterations without changing any of your tool definitions, permission policies, or agent event listeners.

Frequently Asked Questions

Questions Developers Ask About Google Agent Development Kit (ADK) Alternatives

Q:Does Smoke Monkey support Gemini 2.0 Flash and Gemini 1.5 Pro?

Yes. All Gemini variants supported by the Google Generative AI API are accessible by setting `provider: "gemini"` and specifying the model name.

Switch to Smoke Monkey Harness Today

Build autonomous coding agents with zero runtime dependencies, deterministic 6-phase loops, and Model Context Protocol (MCP) in pure TypeScript.

npm install smoke-monkey-harness