by garylab · MCP Server · ★ 488
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Make Money With AI Make Money With AI is a curated list of AI tools and projects that help you turn open-source into income. AutoGPT Use autonomous agents, task automation, and extensible plugin integrations to build commercially scalable SaaS, automated services, marketplace products, and monetizable workflow solutions via prompt engineering. stable-diffusion-webui Provides a production-ready AI-image web UI with custom-models, batch-processing, plugins, and exportable commercial-assets, enabling rapid monetization via services, prints, licensing, merchandise, marketplaces, subscriptions, ads, API-integrations. JavaGuide Comprehensive Java and backend interview guide enables monetization via corporate training, paid courses, developer upskilling, recruitment services, system design consulting, and AI product acceleration strategies. ollama Deploy and monetize private LLMs locally or in enterprise: run gpt-oss, DeepSeek-R1, Gemma 3 for low-cost inference, API integration, scaling, billing, analytics, and fine-tuning capabilities. transformers Leverages pretrained NLP
| Stars | 488 |
| Forks | 98 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 31.15/100 |
| Open Issues | 3 |
| Last Updated | 2026-06-21 |
| Created | 2025-03-19 |
| Platforms | mcp, python |
| Est. Tokens | ~25k |
These tools work well together with MakeMoneyWithAI for enhanced workflows:
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MakeMoneyWithAI is A list of open-source AI projects you can use to generate income easily.. It is categorized as a MCP Server with 488 GitHub stars.
MakeMoneyWithAI is primarily written in Python. It covers topics such as ai, ai-agent, ai-agents.
You can find installation instructions and usage details in the MakeMoneyWithAI GitHub repository at github.com/garylab/MakeMoneyWithAI. The project has 488 stars and 98 forks, indicating an active community.
The top alternatives to MakeMoneyWithAI on Agent Skills Hub include superglue, agents, golf. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.