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.

Official NPM Registry Index

5 Active Packages100% MIT Open Source

Official Smoke Monkey NPM Packages Directory

Install and integrate Smoke Monkey tools directly into your Node.js, Next.js, and TypeScript applications. From our zero-dependency core agent harness and stdio Model Context Protocol (MCP) server to our streaming React canvas, explore all official packages published on the global npm registry.

Quick Install Summary

How to Install Smoke Monkey Packages via NPM & NPX

Smoke Monkey publishes 5 packages on the public npm registry. To build autonomous AI coding agents, run:

Scoped MCP Package • v1.1.0

View on NPM

Scoped alias package for the Model Context Protocol (MCP) server distribution, supporting standard npm library imports and custom server lifecycle hooks.

$ npm install @smoke-monkey/mcpNode.js 18+

Scoped PackageMCP StdioServer Lifecycle

Read Documentation

End-to-End Example

How to Combine Smoke Monkey Packages in One Project

Install the core runtime and React chat canvas together to spin up an autonomous agent with a full streaming UI:

fullstack-agent.tstypescript

1// 1. Install packages:
2// npm install smoke-monkey-harness @smoke-monkey/ui
3
4import { createAgent } from 'smoke-monkey-harness';
5import { AgentCanvas } from '@smoke-monkey/ui';
6
7// 2. Initialize Agent with Local File Tools & Guardrails
8export const agent = createAgent({
9  workspacePath: process.cwd(),
10  provider: 'anthropic',
11  model: 'claude-3-5-sonnet-latest',
12  maxLoops: 25,
13  permissions: {
14    run_command: 'ask',            // The Three Pauses: pause for human approval
15    replace_file_content: 'allow', // Surgical AST code modification
16  },
17});
18
19// 3. Optional: Attach as Model Context Protocol (MCP) server
20// claude mcp add smoke-monkey npx -y smoke-monkey-harness-mcp

Open Source Ecosystem

Ready to Ship Agentic Software?

Explore the quickstart documentation to see how Smoke Monkey Harness replaces chaotic ReAct prompts with deterministic, zero-dependency engineering pipelines.