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MAHORAGA

autonomous trading agent powered by social sentiment analysis and ai that learns, grows, and adapts

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Install / Use

/learn @ygwyg/MAHORAGA
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

⚠️ Warning: This software is provided for educational and informational purposes only. Nothing in this repository constitutes financial, investment, legal, or tax advice.

MAHORAGA

An autonomous, LLM-powered trading agent that runs 24/7 on Cloudflare Workers.

Discord

MAHORAGA monitors social sentiment from StockTwits and Reddit, uses AI (OpenAI, Anthropic, Google, xAI, DeepSeek via AI SDK) to analyze signals, and executes trades through Alpaca. It runs as a Cloudflare Durable Object with persistent state, automatic restarts, and 24/7 crypto trading support.

<img width="1278" height="957" alt="dashboard" src="https://github.com/user-attachments/assets/56473ab6-e2c6-45fc-9e32-cf85e69f1a2d" />

Features

  • 24/7 Operation — Runs on Cloudflare Workers, no local machine required
  • Multi-Source Signals — StockTwits, Reddit (4 subreddits), Twitter confirmation
  • Multi-Provider LLM — OpenAI, Anthropic, Google, xAI, DeepSeek via AI SDK or Cloudflare AI Gateway
  • Crypto Trading — Trade BTC, ETH, SOL around the clock
  • Options Support — High-conviction options plays
  • Staleness Detection — Auto-exit positions that lose momentum
  • Pre-Market Analysis — Prepare trading plans before market open
  • Discord Notifications — Get alerts on BUY signals
  • Pluggable Strategy System — Create custom strategies without touching core files

Requirements

  • Node.js 18+
  • Cloudflare account (free tier works)
  • Alpaca account (free, paper trading supported)
  • LLM API key (OpenAI, Anthropic, Google, xAI, DeepSeek) or Cloudflare AI Gateway credentials

Quick Start

1. Clone and install

git clone https://github.com/ygwyg/MAHORAGA.git
cd mahoraga
npm install

2. Create Cloudflare resources

# Create D1 database
npx wrangler d1 create mahoraga-db
# Copy the database_id to wrangler.jsonc

# Create KV namespace
npx wrangler kv namespace create CACHE
# Copy the id to wrangler.jsonc

# Run migrations
npx wrangler d1 migrations apply mahoraga-db

3. Set secrets

# Required
npx wrangler secret put ALPACA_API_KEY
npx wrangler secret put ALPACA_API_SECRET

# API Authentication - generate a secure random token (64+ chars recommended)
# Example: openssl rand -base64 48
npx wrangler secret put MAHORAGA_API_TOKEN

# LLM Provider (choose one mode)
npx wrangler secret put LLM_PROVIDER  # "openai-raw" (default), "ai-sdk", or "cloudflare-gateway"
npx wrangler secret put LLM_MODEL     # e.g. "gpt-4o-mini" or "anthropic/claude-sonnet-4"

# LLM API Keys (based on provider mode)
npx wrangler secret put OPENAI_API_KEY         # For openai-raw or ai-sdk with OpenAI
npx wrangler secret put OPENAI_BASE_URL        # Optional: override OpenAI base URL for openai-raw and ai-sdk (OpenAI models)
# npx wrangler secret put ANTHROPIC_API_KEY    # For ai-sdk with Anthropic
# npx wrangler secret put GOOGLE_GENERATIVE_AI_API_KEY  # For ai-sdk with Google
# npx wrangler secret put XAI_API_KEY          # For ai-sdk with xAI/Grok
# npx wrangler secret put DEEPSEEK_API_KEY     # For ai-sdk with DeepSeek
# npx wrangler secret put CLOUDFLARE_AI_GATEWAY_ACCOUNT_ID  # For cloudflare-gateway
# npx wrangler secret put CLOUDFLARE_AI_GATEWAY_ID          # For cloudflare-gateway
# npx wrangler secret put CLOUDFLARE_AI_GATEWAY_TOKEN       # For cloudflare-gateway

# Optional
npx wrangler secret put ALPACA_PAPER         # "true" for paper trading (recommended)
npx wrangler secret put TWITTER_BEARER_TOKEN
npx wrangler secret put DISCORD_WEBHOOK_URL
npx wrangler secret put KILL_SWITCH_SECRET   # Emergency kill switch (separate from API token)

4. Deploy

npx wrangler deploy

5. Enable the agent

All API endpoints require authentication via Bearer token:

# Set your API token as an env var for convenience
export MAHORAGA_TOKEN="your-api-token"

# Enable the agent
curl -H "Authorization: Bearer $MAHORAGA_TOKEN" \
  https://mahoraga.bernardoalmeida2004.workers.dev/agent/enable

6. Monitor

# Check status
curl -H "Authorization: Bearer $MAHORAGA_TOKEN" \
  https://mahoraga.bernardoalmeida2004.workers.dev/agent/status

# View logs
curl -H "Authorization: Bearer $MAHORAGA_TOKEN" \
  https://mahoraga.bernardoalmeida2004.workers.dev/agent/logs

# Emergency kill switch (uses separate KILL_SWITCH_SECRET)
curl -H "Authorization: Bearer $KILL_SWITCH_SECRET" \
  https://mahoraga.bernardoalmeida2004.workers.dev/agent/kill

# Run dashboard locally
cd dashboard && npm install && npm run dev

Local Development

# Terminal 1 - Start wrangler
npx wrangler dev

# Terminal 2 - Start dashboard  
cd dashboard && npm run dev

# Terminal 3 - Enable the agent
curl -H "Authorization: Bearer $MAHORAGA_TOKEN" \
  http://localhost:8787/agent/enable

Custom Strategies

Mahoraga uses a pluggable strategy system. The core harness is a thin orchestrator — all customizable logic lives in strategy modules. You never need to modify core files.

How it works

  1. Create src/strategy/my-strategy/index.ts implementing the Strategy interface
  2. Change one import line in src/strategy/index.ts
// src/strategy/index.ts
import { myStrategy } from "./my-strategy";
export const activeStrategy = myStrategy;

What you can customize

| Component | File | What it does | |-----------|------|--------------| | Gatherers | gatherers/*.ts | Fetch signals from data sources (StockTwits, Reddit, etc.) | | Prompts | prompts/*.ts | LLM prompt templates for research and analysis | | Entry rules | rules/entries.ts | Decide which signals to buy | | Exit rules | rules/exits.ts | Decide when to sell positions | | Config | config.ts | Default parameters and source weights |

You can reuse default gatherers, mix in custom ones, override prompts, and define your own entry/exit rules — all without touching core files.

Adding a new data source

Create a gatherer that returns Signal[]:

import type { Gatherer, StrategyContext } from "../../types";

const myGatherer: Gatherer = {
  name: "my-source",
  gather: async (ctx: StrategyContext) => {
    const res = await fetch("https://your-api.com/data");
    const data = await res.json();
    return data.items.map(item => ({
      symbol: item.ticker,
      source: "my_source",
      source_detail: "my_source_v1",
      sentiment: item.sentiment,
      raw_sentiment: item.sentiment,
      volume: 1,
      freshness: 1.0,
      source_weight: 0.9,
      reason: `MySource: ${item.summary}`,
      timestamp: Date.now(),
    }));
  },
};

Then include it in your strategy's gatherers array.

See docs/harness.html for the full customization guide.

Configuration

| Setting | Default | Description | |---------|---------|-------------| | max_positions | 5 | Maximum concurrent positions | | max_position_value | 5000 | Maximum $ per position | | take_profit_pct | 10 | Take profit percentage | | stop_loss_pct | 5 | Stop loss percentage | | min_sentiment_score | 0.3 | Minimum sentiment to consider | | min_analyst_confidence | 0.6 | Minimum LLM confidence to trade | | options_enabled | false | Enable options trading | | crypto_enabled | false | Enable 24/7 crypto trading | | llm_model | gpt-4o-mini | Research model (cheap, for bulk analysis) | | llm_analyst_model | gpt-4o | Analyst model (smart, for trading decisions) |

LLM Provider Configuration

MAHORAGA supports multiple LLM providers via three modes:

| Mode | Description | Required Env Vars | |------|-------------|-------------------| | openai-raw | Direct OpenAI API (default) | OPENAI_API_KEY | | ai-sdk | Vercel AI SDK with 5 providers | One or more provider keys | | cloudflare-gateway | Cloudflare AI Gateway (/compat) | CLOUDFLARE_AI_GATEWAY_ACCOUNT_ID, CLOUDFLARE_AI_GATEWAY_ID, CLOUDFLARE_AI_GATEWAY_TOKEN |

Optional OpenAI Base URL Override:

  • OPENAI_BASE_URL — Override the base URL used for OpenAI requests. Applies to LLM_PROVIDER=openai-raw and OpenAI models in LLM_PROVIDER=ai-sdk (models starting with openai/). Default: https://api.openai.com/v1.

Cloudflare AI Gateway Notes:

  • This integration calls Cloudflare's OpenAI-compatible /compat/chat/completions endpoint and always sends cf-aig-authorization.
  • It is intended for BYOK/Unified Billing setups where upstream provider keys are configured in Cloudflare (so your worker does not send provider API keys).
  • Models use the {provider}/{model} format (e.g. openai/gpt-5-mini, google-ai-studio/gemini-2.5-flash, anthropic/claude-sonnet-4-5).

AI SDK Supported Providers:

| Provider | Env Var | Example Models | |----------|---------|----------------| | OpenAI | OPENAI_API_KEY | openai/gpt-4o, openai/o1 | | Anthropic | ANTHROPIC_API_KEY | anthropic/claude-sonnet-4, anthropic/claude-opus-4 | | Google | GOOGLE_GENERATIVE_AI_API_KEY | google/gemini-2.5-pro, google/gemini-2.5-flash | | xAI (Grok) | XAI_API_KEY | xai/grok-4, xai/grok-3 | | DeepSeek | DEEPSEEK_API_KEY | deepseek/deepseek-chat, deepseek/deepseek-reasoner |

Example: Using Claude with AI SDK:

npx wrangler secret put LLM_PROVIDER      # Set to "ai-sdk"
npx wrangler secret put LLM_MODEL         # Set to "anthropic/claude-sonnet-4"
npx wrangler secret put ANTHROPIC_API_KEY # Your Anthropic API key

API Endpoints

| Endpoint | Description | |----------|-------------| | /agent/status | Full status (account, positions, signals) | | /agent/enable | Enable the agent | | /agent/disable | Disable the agent | | /agent/config | Get or update configuration | | /agent/logs | Get recent logs | | /agent/trigger | Manually trigger (for testing) | | /agent/kill | Emergency kill switch (uses KILL_SWITCH_SECRET) | | /mcp | MCP server for tool ac

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ygwyg/MAHORAGA

Languages

TypeScript

Security Score

80/100

Audited on Apr 8, 2026

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