+12 Monkeys

Agent-as-a-Service Platform with MCP Integration

Build and deploy custom AI agents in under 10 minutes through conversational configuration.

     

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What is +12 Monkeys?

+12 Monkeys is a plug-and-play platform that enables developers to create, configure, and deploy production-ready AI agent systems without writing code. Simply describe what you need in natural language, and the platform generates a complete deployable package — Python, TypeScript, Rust, or Go — ready to deploy with docker compose up, Railway, Render, or Vercel.

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Key Features

	Feature	Description
💬	Conversational Config	No code required — just describe what you need in plain English
🔌	MCP-Native	Built on Model Context Protocol (Linux Foundation standard)
🎨	20 Agent Templates	Customer service, research, data analysis, code gen, multi-agent teams, and 15 more
🚀	3 Deploy Targets	LOCAL (Docker Compose) · CLOUD (Railway / Render / Vercel) · EXPORT (self-host)
🔧	Multi-Framework	LangGraph · CrewAI · AutoGen · Semantic Kernel · Vercel AI SDK · Rig · ADK-Go

Supported Languages

	Language	Output
🐍	Python	agent.py · requirements.txt · Dockerfile (3.12) · docker-compose.yml
📘	TypeScript	agent.ts · package.json · tsconfig.json · Dockerfile (Node 22)
🦀	Rust	src/main.rs · Cargo.toml · multi-stage Dockerfile (1.84)
🐹	Go	main.go · go.mod · multi-stage Dockerfile (1.23 → distroless)

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📦 What You Receive

Every generated agent package includes production-ready files tailored to the selected language and deployment target:

Python Packages (LangGraph / CrewAI / AutoGen / Semantic Kernel)

File	Description
agent.py	Framework-specific agent code with multi-agent workflows
requirements.txt	Python dependencies (framework SDK, anthropic, mcp, dotenv)
Dockerfile	Python 3.12-slim container (+ Node.js if MCP servers need npx)
docker-compose.yml	One-command deployment with env loading + port mapping
.env.example	Environment variable template with all required keys
mcp-config.json	MCP server configuration
README.md	Setup instructions for Docker and local development

TypeScript Packages (Vercel AI SDK)

File	Description
agent.ts	TypeScript agent using Vercel AI SDK with multi-agent pipeline
package.json	Node.js dependencies (ai, @ai-sdk/anthropic, zod, tsx)
tsconfig.json	TypeScript compiler config (ES2022, ESM)
Dockerfile	Node.js 22-slim container
docker-compose.yml	One-command deployment with env loading + port mapping
.env.example	Environment variable template with all required keys
mcp-config.json	MCP server configuration
README.md	Setup instructions for Docker and local development

Rust Packages (Rig)

File	Description
src/main.rs	Async Rust agent using Rig crate with tokio runtime
Cargo.toml	Rust dependencies (rig-core, tokio, serde, dotenv)
Dockerfile	Multi-stage build: rust:1.84 builder → debian:bookworm-slim runtime
docker-compose.yml	One-command deployment with env loading + port mapping
.env.example	Environment variable template with all required keys
mcp-config.json	MCP server configuration
README.md	Setup instructions for Docker and local Rust development

Go Packages (ADK-Go)

File	Description
main.go	Go agent using Google ADK-Go with goroutine pipeline
go.mod	Go dependencies (google/adk-go, godotenv)
Dockerfile	Multi-stage build: golang:1.23-alpine → distroless runtime
docker-compose.yml	One-command deployment with env loading + port mapping
.env.example	Environment variable template with all required keys
mcp-config.json	MCP server configuration
README.md	Setup instructions for Docker and local Go development

Cloud Deployment Configs (CLOUD / EXPORT targets)

File	Description
railway.toml	Railway deployment config (auto-detects Python/Node/Rust/Go runtime)
render.yaml	Render Blueprint spec with health checks and env vars
vercel.json	Vercel serverless config with function routes
k8s/deployment.yaml	Kubernetes Deployment with replicas, resource limits, probes
k8s/service.yaml	Kubernetes Service (ClusterIP) exposing port 80 → 8080
sam/template.yaml	AWS SAM template with Lambda function + API Gateway