Quickstart

Get from zero to your first AI call in under 5 minutes. Pick your integration method below.

Direct API

MCP / IDE

CLI Tool

Direct API Integration

Use standard HTTP requests to call any supported LLM through a single endpoint. Compatible with any language or framework.

1 Get Your API Key

Lost your API key? We can send a recovery link to your registered email. Your old key will be revoked and a new one issued instantly. Recover your key →

2 Make Your First Call

curl

# Your first API call
curl -X POST https://api.monstergaming.ai/v1/messages \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "monster-gpt",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello from Monster Gaming!"}
    ]
  }'

Tip: You can use friendly model names like sonnet, opus, haiku, gpt-4o, gemini, or deepseek. We resolve them to the latest version automatically.

3 Streaming

For real-time streaming responses (SSE), use the /v1/stream endpoint:

curl

curl -N -X POST https://api.monstergaming.ai/v1/stream \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "monster-gpt",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Write a short game design doc for a puzzle game."}
    ]
  }'

4 Structured Output

Get guaranteed JSON matching your schema via /v1/structured. Works across all providers — we adapt the constraint method per model.

curl

curl -X POST https://api.monstergaming.ai/v1/structured \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "sonnet",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Describe a fantasy RPG enemy."}
    ],
    "response_format": {
      "type": "json_schema",
      "json_schema": {
        "name": "enemy",
        "schema": {
          "type": "object",
          "properties": {
            "name": {"type": "string"},
            "hp": {"type": "integer"},
            "abilities": {
              "type": "array",
              "items": {"type": "string"}
            },
            "weakness": {"type": "string"}
          },
          "required": ["name", "hp", "abilities", "weakness"]
        }
      }
    }
  }'

Schema format: Uses the OpenAI response_format convention. response_format.json_schema.schema must be a valid JSON Schema object. Works with OpenAI, Anthropic, Google, and all other supported providers.

Supported Models

Friendly Name	Provider	Tier Required
`monster-gpt`	Monster Gaming auto-routed (85 domain experts)	Free+
`haiku`	Anthropic Claude Haiku 4.5	Free+
`sonnet`	Anthropic Claude Sonnet 4.6	Starter+
`opus`	Anthropic Claude Opus 4.6	Pro+
`gpt-4o`	OpenAI GPT-4o	Starter+
`gemini`	Google Gemini 3.1 Pro	Free+ (default)
`deepseek`	DeepSeek Chat	Starter+
`mistral`	Mistral Large	Starter+

Try Monster-GPT Chat

Response Format

Responses follow the Anthropic Messages API format:

json

{
  "id": "msg_01XFDUDYJgAACzvnptvVoYEL",
  "type": "message",
  "role": "assistant",
  "content": [
    {"type": "text", "text": "Hello! How can I help with your game?"}
  ],
  "model": "claude-sonnet-4-6-20250514",
  "usage": {"input_tokens": 12, "output_tokens": 15}
}

Error Handling

All errors return JSON with error, code, and message fields. Common status codes:

401 — Invalid or missing API key
403 — Model not available on your tier
429 — Rate limit exceeded (check Retry-After header)
503 — Maintenance mode (check eta field)

All API Endpoints

Complete reference for every endpoint available at api.monstergaming.ai.

POST/v1/messages

Send a chat completion request. Returns a single Anthropic Messages-format response.

Auth: Bearer token required

POST/v1/stream

Streaming chat completion via Server-Sent Events (SSE). Same request body as /v1/messages.

Auth: Bearer token required

POST/v1/structured

Structured JSON output. Requires response_format.json_schema.schema in the request body. Adapts per provider.

Auth: Bearer token required

GET/v1/models

List all models available on your tier. OpenAI-compatible format.

Auth: Bearer token required

GET/v1/disciplines

List AI disciplines (game design, VFX, animation, etc.) available on your tier, plus what upgrading unlocks.

Auth: Bearer token required

GET/v1/whoami

Validate your API key and see your tier, environment, rate limit, and daily spend cap. No rate limit consumed.

Auth: Bearer token required

GET/v1/health

Health check. Returns worker status, version, and environment. No authentication required.

Auth: None

Whoami Example

Quick way to verify your key and check your account status:

curl

curl https://api.monstergaming.ai/v1/whoami \
  -H "Authorization: Bearer YOUR_API_KEY"

response

{
  "tier": "starter",
  "environment": "live",
  "game_id": "my-puzzle-game",
  "rate_limit": 60,
  "daily_cap_cents": 500
}

Models List Example

curl

curl https://api.monstergaming.ai/v1/models \
  -H "Authorization: Bearer YOUR_API_KEY"

Disciplines Example

curl

curl https://api.monstergaming.ai/v1/disciplines \
  -H "Authorization: Bearer YOUR_API_KEY"

response

{
  "object": "list",
  "tier": "starter",
  "count": 12,
  "data": [
    {"id": "general", "available": true},
    {"id": "game-design", "available": true},
    {"id": "narrative", "available": true}
  ],
  "upgrade_unlocks": [
    {"tier": "pro", "total": 25, "new": 13}
  ]
}

MCP Server Setup

Use Monster Gaming as an MCP server in Claude Code, Cursor, or any MCP-compatible IDE. One config, all models.

1 Claude Code

Add to your ~/.claude/settings.json:

json

{
  "mcpServers": {
    "monster-gaming": {
      "url": "https://api.monstergaming.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

2 Cursor / VS Code

Add to your .cursor/mcp.json or VS Code MCP settings:

json

{
  "servers": {
    "monster-gaming": {
      "type": "streamable-http",
      "url": "https://api.monstergaming.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

3 Verify Connection

Once configured, you should see Monster Gaming tools available in your IDE. Test with:

prompt

# In Claude Code or Cursor, ask:
"Use Monster Gaming to generate a player movement script for Unreal Engine 5"

Note: MCP integration provides tool-use capabilities beyond raw chat — including game asset generation, code review tuned for game engines, and project-aware context.

Monster CLI

A command-line tool for quick interactions, key management, and usage monitoring.

1 Install

bash

# Install via npm (Node 18+)
npm install -g @monstergaming/cli

# Or download the binary
curl -fsSL https://monstergaming.ai/install.sh | sh

2 Login

bash

# Login with your API key
monster login
# Enter your API key when prompted

# Or set it via environment variable
export MONSTER_API_KEY=mg_live_xxxx

3 Ask Questions

bash

# Quick one-shot question
monster ask "How do I implement A* pathfinding in UE5?"

# Choose a specific model
monster ask --model opus "Review this blueprint for performance issues"

# Pipe code for review
cat PlayerController.cpp | monster ask "Find bugs in this code"

4 Manage Keys & Usage

bash

# List your API keys
monster keys

# Check usage for current billing period
monster usage

# Generate a new sandbox key
monster keys create --env sandbox

# Test connectivity
monster test

Tip: Use monster ask --stream for real-time streaming output, just like the API's /v1/stream endpoint.