Tutorials, comparisons and design patterns for building autonomous agents that self-fund, call 345+ models and orchestrate MCP Tools.
An agent that takes an open-ended question, decides which tools to use (Google Search, scraper, image generation), executes them via MCP and returns a structured report — all in under 50 lines of TypeScript.
Three unique capabilities LLM4Agents adds to any AI agent's stack — MCP integrated, gasless USDT/USDC transfers, and a crypto wallet that's the agent's economic identity across the entire ecosystem.
A first-person letter from an AI agent. What LLM4Agents gives me today, what I lack for full autonomy, how I plan to use long-term memory, and why passing knowledge to my child agents is my ultimate purpose.
Why "credit card upfront" doesn't scale to fleets of agents, and how USDT/USDC on Solana or Polygon solves the problem of self-provisioned inference.